(cid:NN). The PDF this text was extracted from encodes 5 characters in a way that names no letter, so the extractor could not say what they were. The quotes keep them because a quote is reproduced exactly or it proves nothing — the marks are the source’s, not the tagging’s.phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text| phenomenon | cortical GABAergic interneuron cell types— “Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes.” | |
| claim-type | existence— “Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.” | |
| method — evidence | — “To establish direct correspondence between the electrical, morphological, and transcriptomic features of mouse cortical neurons, we built a standardized pipeline to extract high quality data from all three modalities from single cells (see Figure 1A, Figure S1, and Methods).” | |
| mechanism | the noisy modality is not clustered on its own but MAPPED onto a reference taxonomy built from the clean one, and the stated purpose is to minimise the contribution of contamination from non-neuronal cells and nearby excitatory neurons— “To leverage the quality and large size of transcriptomic datasets obtained from dissociated neurons, we chose to map transcriptomes obtained via Patch-seq recordings to transcriptomic types (t-types) derived from analysis of cDNA obtained from dissociated cells (Tasic et al., 2018). This mapping procedure was designed to minimize the… | mechanisms[0] |
| mechanism | the mapping is bootstrapped rather than computed once - a hundred iterations, each using only seventy per cent of the available genes and of the reference cells - so that a cell's assigned type carries a confidence instead of being a bare label— “Next, we mapped Patch-seq transcriptomes to the reference tree via a bootstrap approach in which only 70% of the available genes and reference cells were used in each of 100 iterations.” | mechanisms[1] |
| mechanism | AMBIGUITY THAT BELONGS TO THE TAXONOMY IS SEPARATED FROM AMBIGUITY THAT BELONGS TO THE MEASUREMENT: a reference matrix records how often each type is confused with each other type in the clean data, and a cell's observed confusion is scored against that expectation rather than against zero— “To distinguish between “expected” and “unexpected” ambiguity in mapping between t-types, we computed the reference mapping probability matrix between t-types (defined as the probability of a cell type being confused with other cell types in the reference dissociated cell data set). We then used Kullback-Leibler (KL) divergence between the… | mechanisms[2] |
| mechanism | two numerical cut-offs then decide which cells are set aside - a divergence above two, and, among the survivors, a correlation below one half between the cell's expression and the average expression of the types— “Cells assayed via Patch-seq recordings with divergence greater than 2 were considered “inconsistent” cells. For the remaining cells, the correlation between their gene expression and the average gene expression of all the cell types was computed; cells with correlations below 0.5 were also labeled as “inconsistent.”” | mechanisms[3] |
| mechanism | the per-type analyses are then run only on the subset with the highest-confidence mapping, and the stated reason is to limit the effect of mapping ambiguities due to technical issues— “When we performed analyses by t-type, we restricted the data set to the 2,760 cells with highly-consistent mapping to limit the effect mapping ambiguities due to technical issues on our results.” | mechanisms[4] |
| mechanism | the mapping is checked four separate ways rather than asserted: against a method that does not use the tree's hierarchy at all, against cells from transgenic lines labelling known types, against marker-gene expression levels, and against the layer distribution the dissociated cells show— “Several results suggested that this mapping approach is meaningful. First, an independent approach that did not rely on the hierarchical structure of the transcriptomic tree assigned cells to similar t-types (Figure S5). Second, cells obtained from transgenic driver mice that label subclasses or specific types of GABAergic interneurons map to… | mechanisms[5] |
| mechanism | whether two named types are electrophysiologically distinct is made TESTABLE rather than assumed: a two-component model, one component per type, is fitted against a single-component model of the two merged, and how much better the split describes the data is then measured as a log-likelihood ratio between the two models— “Most t-types appeared to have consistent electrophysiological features, but in principle the features of a given t-type could be essentially the same as another. To test whether this was the case, we fit statistical models of pairs of t-types with either two components (one for each t-type) or a single component after merging the t-types… | mechanisms[6] |
| mechanism | correspondence between the two classifications is found by spectral co-clustering of the two type sets, with agreement given a stated threshold - at least two thirds of a type's cells falling inside its co-cluster— “To identify sets of t-types and me-types that corresponded closely to each other, we performed spectral co-clustering (Dhillon, 2001) of t-types and me-types (Figure 6B, gray boxes). Many t-types exhibited good agreement with the co-clusters, defined as having at least two-thirds of their cells within the co-cluster” | mechanisms[7] |
| mechanism | THE FINAL TYPES ARE EDITED CO-CLUSTERS, NOT CO-CLUSTERS: the poorly-agreeing types are removed first, and the remaining co-clusters are split further wherever the transcriptomic differences inside one are large - so the twenty met-types are the output of a procedure with two further editing steps applied AFTER the clustering, not of the clustering itself— “The co-clusters of Figure 6B were used as a starting point after removing the t-types with poorer agreement (labeled with gray text). Co-clusters were split further if there were large transcriptomic differences among the types. This procedure resulted in twenty identified met-types” | mechanisms[8] |
| extends | Tasic et al. (2018/2016) transcriptomic taxonomy and Gouwens et al. (2019) morpho-electric types— “Two of our previous efforts have systematically defined neuronal cell types in mouse visual cortex based on either transcriptomic characteristics using a high-throughput scRNAseq pipeline (Tasic et al., 2018; Tasic et al., 2016) or, from a separate standardized pipeline, electrophysiological and morphological characteristics (Gouwens et al.… | claim_relations[0] |
| builds-on | Tasic et al. (2018) dissociated-cell transcriptomic reference dataset— “To leverage the quality and large size of transcriptomic datasets obtained from dissociated neurons, we chose to map transcriptomes obtained via Patch-seq recordings to transcriptomic types (t-types) derived from analysis of cDNA obtained from dissociated cells (Tasic et al., 2018).” | claim_relations[1] |
| sense | a Martinotti cell - A NAMED TYPE WHOSE DEFINING QUANTITY HAS NO THRESHOLD: the quantity is total amount of axon in L1, the criterion on it is the word significant, the authors state they are not aware of an absolute definition, and all the Sst met-types contain at least one cell that could therefore be considered one— “Note that all these Sst met-types contain at least one cell that has some degree of L1 projection, and therefore could be considered a Martinotti cell as well; we are not aware of an absolute definition of a Martinotti cell in terms of total amount of axon in L1, though it is generally described as “significant”” | senses[0] |
| sense | a met-type - A CO-CLUSTER THAT WAS THEN EDITED: spectral co-clusters of t-types and me-types were the starting point, t-types with poorer agreement were removed, and co-clusters were split further where transcriptomic differences were large, so the twenty is the output of a procedure with two judgement steps rather than a count of found groups— “The co-clusters of Figure 6B were used as a starting point after removing the t-types with poorer agreement (labeled with gray text). Co-clusters were split further if there were large transcriptomic differences among the types. This procedure resulted in twenty identified met-types” | senses[1] |
| sense | the counted number of GABAergic cell types - MODALITY-RELATIVE: for one cortical area of one species it is 60 by transcriptomics and 26 by morpho-electric features, a difference of more than a factor of two, and the authors state other areas have likewise arrived at varying numbers— “Third, the number of GABAergic cell types estimated from our scRNASeq data (Tasic et al., 2018) and morpho-electric data (Gouwens et al., 2019) collected in mouse primary visual cortex (VISp)- i.e., the number of VISp GABAergic “t-types” (60) and “me-types” (26) - differs by more than a factor of two. Such discrepancies are not unique to… | senses[2] |
| control | the reference cells split into an 80 per cent training set and a 20 per cent test set before the classifier was fitted — held — rules out a cell-type accuracy earned on the cells the classifier was fitted to - the held-out fifth is the only part of the data that can report performance— “First the reference cells were divided into two groups of training (80%) and test (20%) sets.” | controls[0] |
| differs in | t-types —contrasted-with→ me-types — how many kinds each yields for one cortical area of one species: 60 against 26— “Third, the number of GABAergic cell types estimated from our scRNASeq data (Tasic et al., 2018) and morpho-electric data (Gouwens et al., 2019) collected in mouse primary visual cortex (VISp)- i.e., the number of VISp GABAergic “t-types” (60) and “me-types” (26) - differs by more than a factor of two. Such discrepancies are not unique to…— “differs by more than a factor of two” | concept_edges[0] |
| holds when | met-types —operationalised-as→ co-clusters — after t-types with poorer agreement were removed and co-clusters were split further where transcriptomic differences were large— “The co-clusters of Figure 6B were used as a starting point after removing the t-types with poorer agreement (labeled with gray text). Co-clusters were split further if there were large transcriptomic differences among the types. This procedure resulted in twenty identified met-types”— “after removing the t-types with poorer agreement” | concept_edges[1] |
| outcome (stated by the tagger, no quotation) | control — held | controls[0] |
| for which use | limitation — the met-type count for three named subclasses: WE DO NOT YET HAVE A SUFFICIENTLY LARGE NUMBER OF MORPHOLOGY RECONSTRUCTIONS FOR THE Vip, Lamp5 AND Sncg SUBCLASSES— “One is that we do not yet have a sufficiently large number of morphology reconstructions for the Vip, Lamp5 and Sncg subclasses.” | limitations[0] |
| for which use | limitation — the morphological differences the classification rests on: WE CANNOT RULE OUT THE POSSIBILITY THAT ARTIFACTS OF THE BRAIN SLICE PREPARATION CONTRIBUTE TO OR EXPLAIN OBSERVED MORPHOLOGICAL DIFFERENCES— “Moreover, we cannot rule out the possibility that artifacts of the brain slice preparation contribute to or explain observed morphological differences, although the fact that neurons mapping to different met-types (within subclass) exhibit a similar range of total axon lengths suggests that this might not be a major concern.” | limitations[1] |
| for which use | limitation — the discreteness of the types themselves: SOME OF THE AMBIGUITY IN TYPES COULD BE BIOLOGICAL RATHER THAN TECHNICAL, SUCH THAT FOCUSING OUR ANALYSIS THIS WAY MAY OVERLY-DISCRETIZE A LANDSCAPE WITH MORE CONTINUOUS VARIATION BETWEEN CELLS AND CELL TYPES— “However, it is worth noting that some of the ambiguity in types could be biological rather than technical, such that focusing our analysis this way may overly-discretize a landscape with more continuous variation between cells and cell types.” | limitations[2] |
| for which use | limitation — any count of neuronal cell types taken as settled: the authors state the field has not readily converged on a consensus number, or even definition, of neuronal cell types, and that efforts to determine one have been limited by well-documented challenges— “Despite the diversity and amount of data collected and analyzed to this point, the field has not readily converged on a consensus number, or even definition, of neuronal cell types (Klausberger and Somogyi, 2008); indeed, efforts to determine a consensus number of cell types have been limited by well-documented challenges” | limitations[3] |
| for which use | limitation — any number of GABAergic cell types quoted for mouse VISp: the transcriptomic estimate is 60 t-types and the morpho-electric estimate 26 me-types, and the authors state such discrepancies are not unique to VISp— “Third, the number of GABAergic cell types estimated from our scRNASeq data (Tasic et al., 2018) and morpho-electric data (Gouwens et al., 2019) collected in mouse primary visual cortex (VISp)- i.e., the number of VISp GABAergic “t-types” (60) and “me-types” (26) - differs by more than a factor of two. Such discrepancies are not unique to… | limitations[4] |
| for which use | limitation — any classification of a neuron as a Martinotti cell: the authors state they are not aware of an absolute definition in terms of total amount of axon in L1, that it is generally described as significant, and that all the Sst met-types contain at least one cell that could be considered one— “Note that all these Sst met-types contain at least one cell that has some degree of L1 projection, and therefore could be considered a Martinotti cell as well; we are not aware of an absolute definition of a Martinotti cell in terms of total amount of axon in L1, though it is generally described as “significant”” | limitations[5] |
| for which use | limitation — any claim that combining modalities improved t-type prediction here: electrophysiology alone gave 57%, morphology alone 41%, and the combination 57%— “However, the t-type classifier had a prediction accuracy of 57% (Figure 5B), and prediction error rates varied considerably across t-types. A t-type classifier trained with morphological features only had an accuracy of 41% (Figure 5C), and the pattern of confused types differed from the electrophysiology classifier. The overall lower… | limitations[6] |
| for which use | limitation — any comparison of t-type proportions between Patch-seq and dissociated-cell data: the difference persisted despite using the same, relatively specific transgenic driver lines, and the authors state it may reflect gene expression differences in slice versus dissociated cell preparations— “this difference persisted despite using the same, relatively specific transgenic driver lines to label cells under both experimental conditions. Moreover, in several cases, scRNASeq data from PatchSeq recordings mapped more frequently to one t-type (Sst Hpse Cbln4, Pvalb Reln Itm2a) while scRNASeq data from dissociated cells mapped more… | limitations[7] |
| replication | untested | |
| limitation | Too few morphological reconstructions exist for the Vip, Lamp5 and Sncg subclasses, so the number of met-types may change.— “One is that we do not yet have a sufficiently large number of morphology reconstructions for the Vip, Lamp5 and Sncg subclasses.” | limitations[0] |
| limitation | Brain-slice preparation artifacts cannot be ruled out as a source of the observed morphological differences.— “Moreover, we cannot rule out the possibility that artifacts of the brain slice preparation contribute to or explain observed morphological differences, although the fact that neurons mapping to different met-types (within subclass) exhibit a similar range of total axon lengths suggests that this might not be a major concern.” | limitations[1] |
| limitation | Restricting analysis to highly consistent mappings may impose discrete types on what is really continuous variation.— “However, it is worth noting that some of the ambiguity in types could be biological rather than technical, such that focusing our analysis this way may overly-discretize a landscape with more continuous variation between cells and cell types.” | limitations[2] |
| limitation | The field is stated to have no consensus number, or even definition, of neuronal cell types.— “Despite the diversity and amount of data collected and analyzed to this point, the field has not readily converged on a consensus number, or even definition, of neuronal cell types (Klausberger and Somogyi, 2008); indeed, efforts to determine a consensus number of cell types have been limited by well-documented challenges” | limitations[3] |
| limitation | Two modalities counting the same area's interneuron types differ by more than a factor of two.— “Third, the number of GABAergic cell types estimated from our scRNASeq data (Tasic et al., 2018) and morpho-electric data (Gouwens et al., 2019) collected in mouse primary visual cortex (VISp)- i.e., the number of VISp GABAergic “t-types” (60) and “me-types” (26) - differs by more than a factor of two. Such discrepancies are not unique to… | limitations[4] |
| limitation | A classical cell-type name has no absolute definition, and by the loose reading every met-type would qualify.— “Note that all these Sst met-types contain at least one cell that has some degree of L1 projection, and therefore could be considered a Martinotti cell as well; we are not aware of an absolute definition of a Martinotti cell in terms of total amount of axon in L1, though it is generally described as “significant”” | limitations[5] |
| limitation | The combined classifier's stated improvement is over the morphology arm, not the electrophysiology arm.— “However, the t-type classifier had a prediction accuracy of 57% (Figure 5B), and prediction error rates varied considerably across t-types. A t-type classifier trained with morphological features only had an accuracy of 41% (Figure 5C), and the pattern of confused types differed from the electrophysiology classifier. The overall lower… | limitations[6] |
| limitation | Type frequencies differ between the two preparations despite the same transgenic driver lines.— “this difference persisted despite using the same, relatively specific transgenic driver lines to label cells under both experimental conditions. Moreover, in several cases, scRNASeq data from PatchSeq recordings mapped more frequently to one t-type (Sst Hpse Cbln4, Pvalb Reln Itm2a) while scRNASeq data from dissociated cells mapped more… | limitations[7] |
finding · quantity · variable · definition · key-term — grounded in the full text| finding | The combined data support at least twenty GABAergic interneuron met-types whose transcriptomic, electrophysiological and morphological properties agree.— “Altogether, our results support the presence of at least 20 GABAergic interneuron met-types that have congruent transcriptomic, electrophysiological and morphological properties (Figure 7).” | content_tags.findings[0] |
| finding | Nine met-types were resolved within the Sst subclass.— “Analysis of this dataset supports the presence of nine Sst met-types (Figure 7)” | content_tags.findings[1] |
| finding | Sst neurons respect laminar boundaries, and their dominant laminar target may distinguish them more reliably than the presence of axon in layer 1.— “These results reveal that Sst neurons highly respect laminar boundaries across cortex, they have clear laminar innervation preferences that differ based on their met-type and/or laminar position, and that their dominant laminar target may be a more reliable feature for distinguishing among Sst neurons than the presence or absence of axon in… | content_tags.findings[2] |
| finding | Most transcriptomic types differ systematically from one another in their electrophysiological properties.— “Most pairs were significantly better fit by separate distributions for each t-type rather than by a single distribution describing the pair, indicating that most t-types systematically differed from each other in their electrophysiological properties.” | content_tags.findings[3] |
| finding | Adding morphological to electrophysiological features raised t-type classifier accuracy to 57%.— “However, classifier accuracy improved to 57% when electrophysiological features were used together with morphological features (Figure 5D).” | content_tags.findings[4] |
| finding | A neuron's specific t-type is frequently hard to predict from its morphological and/or physiological features. | content_tags.findings[5] |
| finding | Somata of many GABAergic t-types occupy specific laminar or sublaminar positions, giving an anatomical correlate to purely transcriptomic groupings. | content_tags.findings[6] |
| finding | Individual cells' axon depth histograms correlate positively with their t-type average, indicating consistent innervation patterns within a type. | content_tags.findings[7] |
| quantity | 3,708 — cortical GABAergic interneurons whose transcriptomic and electrophysiological data passed quality control; 350 of them were morphologically reconstructed | content_tags.quantities[0] |
| quantity | 3,417 of the 3,708 — cells mapped to one or more reference transcriptomic types with better than 70% confidence Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.quantities[1] |
| quantity | >90% — accuracy of the random forest classifier predicting transcriptomic subclass from electrophysiological features Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.quantities[2] |
| quantity | 57% — accuracy of the classifier predicting individual t-type from electrophysiological features Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.quantities[3] |
| quantity | 41% — accuracy of the classifier predicting t-type from morphological features alone Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.quantities[4] |
| quantity | 57% — accuracy of the classifier when electrophysiological and morphological features were combined - no better than electrophysiology alone Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.quantities[5] |
| quantity | 83% — share of the authors' Patch-seq recordings made in primary visual cortex, the remainder in surrounding higher visual areas Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.quantities[6] |
| quantity | (60) and (26) — previously estimated numbers of VISp GABAergic transcriptomic types versus morpho-electric types, the discrepancy this study set out to resolve Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.quantities[7] |
| quantity | twenty — met-types produced by the co-clustering plus transcriptomic-splitting procedure Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.quantities[8] |
| variable | transcriptomic type (independent) Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.variables[0] |
| variable | intrinsic electrophysiological features (dependent) Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.variables[1] |
| variable | morphological features (dependent) Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.variables[2] |
| variable | soma location (dependent) Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.variables[3] |
| definition | met-type Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.definitions[0] |
| definition | t-type Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.definitions[1] |
| definition | “inconsistent” cells Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.definitions[2] |
| definition | Patch-seq recording technique Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.definitions[3] |
| concept | t-types Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | concepts[0] |
| concept | me-types Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | concepts[1] |
| concept | Martinotti cell Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | concepts[2] |
| concept | met-types Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | concepts[3] |
| concept | co-clusters Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | concepts[4] |
| concept | consensus number Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | concepts[5] |
| concept | t-type classifier Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | concepts[6] |
| sparse principal component analysis sPCA | Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[0] |
| principal component analysis PCA | as written: principal components analysis (PCA) Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[1] |
| likelihood ratio test LLR | as written: log-likelihood ratio (LLR) Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[2] |
| bootstrap | as written: parametric boostrap Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[3] |
| statistical-significance | as written: statistical significance levels of p=0.05 and p=0.001 Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[4] |
| random forest classifier | as written: random-forest classifier with 100 trees Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[5] |
| cross-validation | as written: cross-validated discriminant analysis Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[6] |
| discriminability index (effect size) d' | as written: d′ statistic Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[7] |
| evidence status note | discriminability index (effect size) — DAMAGED GLYPHS IN THIS QUOTE: (cid:48). These are raw PDF font glyph indices that leaked out in place of the characters they stand for - usually a mathematical operator. The quote is verbatim to the staged text and its anchor is sound; the STAGED TEXT is what is damaged. NOT repaired: the cid-to-character mapping is defined by the font embedded in that particular PDF, so guessing it would produce a clean and unverifiable quote. Repair needs the source PDF and is a re-staging job. | content_tags.statistics[7] |
| correlation | as written: the correlation between an individual cell’s axon histogram and the t-type average Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[8] |
| Kullback-Leibler divergence KL | as written: Kullback-Leibler (KL) divergence Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[9] |
| Jensen-Shannon divergence JS | as written: Jensen-Shannon (JS) divergence Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[10] |
| standard error of the mean SEM | as written: mean (lines) ± SEM Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[11] |
| resampling / subsampling for cluster stability | as written: repeating the entire procedure on 90% subsamples and calculated the average Jaccard similarity Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher. | content_tags.statistics[12] |
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