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Record W4399976754 · doi:10.1038/s41684-024-01395-2

Model matchmaking via the Solve-RD Rare Disease Models & Mechanisms Network (RDMM-Europe)

2024· article· en· W4399976754 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLab Animal · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsMcGill UniversityUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of Neurological Disorders and StrokeThird Health ProgrammeMedical Research CouncilEuropean Commission
KeywordsDiseaseComputer scienceComputational biologyRare diseaseIntensive care medicineMedicineBiologyPathology

Abstract

fetched live from OpenAlex

In biomedical research, particularly for rare diseases (RDs), there is a critical need for model organisms to unravel the mechanistic basis of diseases, perform biomarker studies and develop potential therapeutic interventions. Within Solve-RD, an EU-funded research project with the aim of solving large numbers of previously unsolved RDs, the European Rare Disease Models & Mechanisms Network (RDMM-Europe) has been established.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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