{"id":"W6939938495","doi":"10.6084/m9.figshare.26992318","title":"Additional file 1 of Biological basis of extensive pleiotropy between blood traits and cancer risk","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Proportional hazards model; Breast cancer; Multivariate statistics; Blood test; Multivariate analysis; Cancer; Bayesian multivariate linear regression","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002457689,0.001820679,0.001801502,0.002126053,0.001691718,0.00241347,0.002724012,0.002003826,0.8407655],"category_scores_gemma":[0.03559127,0.0009447905,0.001870445,0.003767144,0.000438846,0.002173528,0.001243924,0.001652948,0.1170308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001193321,"about_ca_system_score_gemma":0.002523892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01302568,"about_ca_topic_score_gemma":0.01804796,"domain_scores_codex":[0.9986029,0.0003554462,0.0001726186,0.0003929136,0.0002644552,0.000211574],"domain_scores_gemma":[0.9690781,0.02553633,0.001293634,0.001586634,0.00182096,0.0006843888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0007464112,0.000172788,0.009261034,0.004335008,0.0002417561,0.0002857751,0.0002003163,0.0009735826,0.0004027093,0.002458491,0.9706999,0.01022224],"study_design_scores_gemma":[0.01768274,0.0009194248,0.09914751,0.00920393,0.001374751,0.002977129,0.001247134,0.009784291,0.002180713,0.04633849,0.8086401,0.0005038934],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003182352,0.00003689384,0.000650957,0.0001542718,0.00003645887,0.00007300133,0.997832,0.0001942074,0.0007041242],"genre_scores_gemma":[0.02198046,0.0003929875,0.01085699,0.001883308,0.0002383393,0.003782978,0.9457303,0.001642616,0.01349198],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8407655,"threshold_uncertainty_score":0.2271286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03169750112107769,"score_gpt":0.2383268675247263,"score_spread":0.2066293664036486,"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."}}