MétaCan
Menu
← Back to cohort
Record W4243443556 · doi:10.21203/rs.3.rs-33088/v2

Genome-wide Variant-based Study of Genetic Effects with the Largest Neuroanatomic Coverage

2020· preprint· en· W4243443556 on OpenAlexfundno aff
Jin Li, Wenjie Liu, Huang Li, Feng Chen, Haoran Luo, Peihua Bao, Yanzhao Li, Hailong Jiang, Yue Gao, Hong Liang, Shiaofen Fang

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringFundamental Research Funds for the Central UniversitiesMedical Center, University of RochesterUniversity of California, IrvineUniversity of California, San FranciscoPfizerUniversity of California, Los AngelesNational Institutes of HealthH. Lundbeck A/SJewish General HospitalCanadian Institutes of Health ResearchHarbin Engineering UniversityUniversity of California, DavisFoundation for the National Institutes of HealthUniversity of Southern CaliforniaEisaiWake Forest UniversityOhio State UniversityNational Natural Science Foundation of ChinaNorthern California Institute for Research and EducationGenentechUniversity of South FloridaUSF Health Byrd Alzheimer's InstituteMcGill UniversityDartmouth CollegeNovartis Pharmaceuticals CorporationCase Western Reserve UniversityIXICONatural Science Foundation of Heilongjiang ProvinceUniversity of PittsburghUniversity of California, San DiegoJohns Hopkins UniversityMinistry of Education, IndiaCleveland ClinicYork UniversityUniversity of RochesterAlzheimer's Disease Neuroimaging InitiativeNorthwestern UniversityBiogenBioClinicaF. Hoffmann-La RocheRush UniversityUniversity of PennsylvaniaYale UniversityU.S. Department of DefenseEli Lilly and CompanyBristol-Myers SquibbBrigham and Women's HospitalAlzheimer's AssociationGeorgetown UniversityServierEmory UniversityMeso Scale Diagnostics
KeywordsGenomeBiologyEvolutionary biologyComputational biologyGeneticsGene

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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 designObservational
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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueResearch Square→Same topicGenomics and Rare Diseases→French-language works237,207→