MétaCan
Menu
Back to cohort
Record W2119097398 · doi:10.1016/j.cell.2015.04.013

Widespread Macromolecular Interaction Perturbations in Human Genetic Disorders

2015· article· en· W2119097398 on OpenAlexaff
Nidhi Sahni, S. Stephen Yi, Mikko Taipale, Juan I. Fuxman Bass, Jasmin Coulombe‐Huntington, Fan Yang, Jian Peng, Jochen Weile, Georgios Ioannis Karras, Yang Wang, I. Kovács, Atanas Kamburov, Irina Krykbaeva, Mandy Hiu Yi Lam, George Tucker, Vikram Khurana, Amitabh Sharma, Yang‐Yu Liu, Nozomu Yachie, Quan Zhong, Yun Shen, Alexandre Palagi, Adriana San‐Miguel, Changyu Fan, Dawit Balcha, Amélie Dricot, Daniel M. Jordan, Jennifer Walsh, Akash Shah, Xinping Yang, Ani K. Stoyanova, Alex Leighton, Michael A. Calderwood, Yves Jacob, Michael E. Cusick, Kourosh Salehi‐Ashtiani, Luke Whitesell, Shamil Sunyaev, Bonnie Berger, Albert-Ĺaszló Barabási, Benoît Charloteaux, David E. Hill, Tong Hao, Frederick P. Roth, Yu Xia, Albertha J.M. Walhout, Susan Lindquist, Marc Vidal

Bibliographic record

VenueCell · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoOntario Institute for Cancer ResearchCanadian Institute for Advanced ResearchMcGill University
FundersNational Institute of General Medical SciencesDana-Farber Cancer InstituteNational Human Genome Research InstituteHoward Hughes Medical Institute
KeywordsBiologyGeneticsEvolutionary biologyComputational biology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations643
Published2015
Admission routes1
Has abstractno

Explore more

Same venueCellSame topicRNA and protein synthesis mechanismsFrench-language works237,207