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Record W4394345312 · doi:10.6084/m9.figshare.23896204

Additional file 3 of Identifying novel regulatory effects for clinically relevant genes through the study of the Greek population

2023· dataset· en· W4394345312 on OpenAlexaff
Konstantinos Rouskas, Efthymia A. Katsareli, Charalampia Amerikanou, Alexandros C. Dimopoulos, Stavros Glentis, Alexandra Kalantzi, Anargyros Skoulakis, Nikolaos I. Panousis, Halit Ongen, Deborah Bielser, Alexandra Planchon, Luciana Romano, Vaggelis Harokopos, Martin Reczko, Panagiotis Moulos, Ioannis Griniatsos, Theodoros Diamantis, Emmanouil T. Dermitzakis, Jiannis Ragoussis, George Dedoussis, Antigone S. Dimas

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeneGeneticsComputational biologyPopulationBiologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Additional file 3: Supplementary Table S17. DEGs by tissue in GM, GTEx-am and GTEx-sm. Supplementary Table S18. S vs V DEGs with discordant direction of gene expression bewteen GM and GTEx-am. Supplementary Table S19. DEGs by obesity status in GM tissues. Supplementary Table S20. DEGs by population in S and V tissue. Supplementary Table S21. ATAC-Seq peaks in GM.

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)0.001
metaresearch head score (Gemma)0.012
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 score0.469
Threshold uncertainty score0.758

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.4690.076

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 head0.048
GPT teacher head0.317
Teacher spread0.269 · 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
Published2023
Admission routes1
Has abstractyes

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