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Record W6912548020 · doi:10.5281/zenodo.2654892

Source Data Images for Figures 3a-d, Fig 4

2019· other· en· W6912548020 on OpenAlexaff

Bibliographic record

VenueFigshare · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsScale (ratio)Data sourceStainingHuman liverPixelPattern recognition (psychology)

Abstract

fetched live from OpenAlex

Source Data Files for Figures 3a-d, 4d STAT5BN642H transforms T-cell subsets, resulting in differential peripheral organ infiltration. Histological analysis using CD3, Ki67 and H&E staining of the skin, lung, liver and brain of 7- to 9-week-old wild type (WT), human STAT5B and human STAT5BN642H mice. Images are representative of three independent experiments. Original magnification: 4x (left panels in C and D), 20× and 40× (insets), scale bars = 100 μm. These images represent Source Data files for Figures 3a-d and 4d. Histological analysis using CD3, Ki67 and H&E staining of the liver of recipient mice transplanted with γδ T-cells from hSTAT5BN642H (n = 2) or WT (n = 1) mice. Original magnification: 20× and 40× (insets), scale bars = 100 μm.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.838
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0040.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.8380.665

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.128
GPT teacher head0.340
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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