{"id":"W4398167265","doi":"10.1101/2024.05.17.594714","title":"The CALERIE™ Genomic Data Resource","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; Pacific Centre for Reproductive Medicine; British Columbia Centre of Excellence for Women's Health; University of British Columbia; Canadian Institute for Advanced Research","funders":"National Cancer Institute; Dartmouth College; Canadian Institute for Advanced Research","keywords":"Resource (disambiguation); Computer science; Data science; Computational biology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007633362,0.001094064,0.002159017,0.004444612,0.001203171,0.003762052,0.00377145,0.002290713,0.1882313],"category_scores_gemma":[0.03823071,0.001143808,0.001025386,0.008774649,0.0006323496,0.001357743,0.003009579,0.002150549,0.1028266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001070757,"about_ca_system_score_gemma":0.006043341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007739056,"about_ca_topic_score_gemma":0.01034387,"domain_scores_codex":[0.9960662,0.0009382986,0.0007995097,0.0009531041,0.000958212,0.0002846971],"domain_scores_gemma":[0.9808066,0.008385691,0.001558052,0.005770793,0.002383373,0.001095439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006981206,0.00006446036,0.003575596,0.002252678,0.0002063824,0.0003031958,0.0001966533,0.0007486581,0.001540335,0.006428819,0.9533269,0.03065819],"study_design_scores_gemma":[0.0008764304,0.00006935948,0.006114807,0.0006393776,0.0001819538,0.0002819925,0.0001006804,0.0005142755,0.0014911,0.01103279,0.9786184,0.00007896039],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003341007,0.0001275256,0.002744094,0.0002290327,0.00005241448,0.0001336452,0.9927038,0.001139409,0.002535946],"genre_scores_gemma":[0.002492728,0.0002029152,0.007467231,0.000342464,0.00004157132,0.001291587,0.9854063,0.0006651031,0.002090107],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1882313,"threshold_uncertainty_score":0.6296965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01892757743533366,"score_gpt":0.2442631928809607,"score_spread":0.225335615445627,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}