{"id":"W2314745348","doi":"10.1158/1055-9965.gwas-ia14","title":"Abstract IA14: Adipose tissue as a rich information source.","year":2012,"lang":"en","type":"article","venue":"Cancer Epidemiology Biomarkers & Prevention","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adipose tissue; Overweight; Cancer; Endocrinology; Medicine; Breast cancer; Internal medicine; Insulin resistance; Obesity; Adipokine; Hormone; Weight loss; Oncology; Bioinformatics; Biology","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":[0.001344837,0.001539796,0.001129237,0.005770316,0.0006369331,0.003492648,0.001779436,0.001184089,0.3255276],"category_scores_gemma":[0.007369236,0.0007077398,0.0007189959,0.007074452,0.0003310134,0.002962209,0.002195023,0.0009235382,0.1680636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008158365,"about_ca_system_score_gemma":0.001420222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00176054,"about_ca_topic_score_gemma":0.001757445,"domain_scores_codex":[0.999201,0.0001820778,0.0001095489,0.0001622897,0.000286163,0.00005898012],"domain_scores_gemma":[0.9961485,0.001391605,0.0002455986,0.0005712652,0.00115112,0.0004918776],"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":[0.0005824245,0.00007112055,0.001030945,0.00266153,0.00007207882,0.0003320437,0.00008317817,0.0007709501,0.009796537,0.008434867,0.8016947,0.1744697],"study_design_scores_gemma":[0.0001190196,0.0001140333,0.003495525,0.0004729883,0.00008820566,0.0003851629,0.00008013743,0.003360747,0.0065946,0.007898482,0.9773297,0.00006132501],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.004045621,0.005420693,0.09190976,0.006659128,0.006810838,0.0008729553,0.745344,0.04906679,0.08987017],"genre_scores_gemma":[0.02678749,0.004041285,0.09934723,0.001349629,0.001612034,0.001223118,0.7364777,0.006135938,0.1230256],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3255276,"threshold_uncertainty_score":0.9620529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02311438608002668,"score_gpt":0.3372863723331215,"score_spread":0.3141719862530948,"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."}}