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.
fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.
VenueLecture notes in computer science · 2024
Typebook
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignUniversity of California, Los AngelesStockholms UniversitetFreie Universität BerlinUniversität BielefeldGenome Institute of SingaporeCentre National de la Recherche ScientifiqueTel Aviv UniversityTsinghua UniversityNational Science FoundationBar-Ilan UniversityRice UniversityNational University of SingaporeCarnegie Mellon UniversityUniversity of Texas Health Science Center at San AntonioUniversity of Texas Southwestern Medical CenterUniversity of Central FloridaUniversità degli Studi di PadovaUniversity of WashingtonPrinceton UniversityJohns Hopkins UniversityMcGill UniversityUniversity of Wisconsin-MadisonBrown UniversityHelsingin YliopistoUniversity of California, San DiegoUniversity of TorontoYale UniversitySeoul National UniversityBroad InstituteIndiana University BloomingtonNational Institutes of HealthGeorgia Institute of TechnologyUniversity of HaifaCalifornia Institute of TechnologyUniversity of PennsylvaniaShanghaiTech UniversityWestlake UniversityUniversity of ConnecticutUniversity of Southern California
KeywordsComputer scienceArtificial intelligenceTheoretical computer science
Abstract
fetched live from OpenAlexNo 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.
Full frame distilled prediction
Teacher imitationNot 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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.968
Codex and Gemma teacher scores by category
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.
Teacher spread0.329 · 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
