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Record W6977409319 · doi:10.6084/m9.figshare.27230030

Additional file 2 of A validated heart-specific model for splice-disrupting variants in childhood heart disease

2024· dataset· en· W6977409319 on OpenAlexaff

Bibliographic record

VenueFigshare · 2024
Typedataset
Languageen
FieldSocial Sciences
TopicHealth, Education, and Cultural Studies
Canadian institutionsLondon Health Sciences CentreMcMaster Children's HospitalChildren's Hospital of Eastern OntarioTed Rogers Centre for Heart ResearchUniversity of TorontoUniversity Health NetworkSickKids FoundationKingston Health Sciences CentreHospital for Sick Children
Fundersnot available
KeywordsConstraint (computer-aided design)GeneTable (database)Heart diseaseAssociation (psychology)Disease

Abstract

fetched live from OpenAlex

Additional file2: Table S2. CHD gene list. Genes were categorized into Tier 1 (moderate to strong association with CHD) or Tier 2 (limited association with CHD). Gene Median gene expression (Transcripts Per Million) was calculated for the entire Discovery cohort. Gene annotations and constraint metrics are additionally shown.

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)0.010
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.468
Threshold uncertainty score0.758

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.4680.120

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 head0.075
GPT teacher head0.349
Teacher spread0.274 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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