{"id":"W2518077473","doi":"10.1160/th16-08-0634","title":"Matching genes with constitution and environment","year":2016,"lang":"en","type":"letter","venue":"Thrombosis and Haemostasis","topic":"Blood Coagulation and Thrombosis Mechanisms","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hamilton General Hospital","funders":"","keywords":"Constitution; Gene; Computational biology; Genetics; Biology; Medicine; Political science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.002258231,0.0004448847,0.001010379,0.0004017588,0.001772917,0.002098228,0.00084054,0.02002948,0.004947995],"category_scores_gemma":[0.02264874,0.0003644297,0.000692039,0.0005767017,0.002893952,0.002796166,0.001626698,0.01656996,0.001646079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001324716,"about_ca_system_score_gemma":0.001260366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001140926,"about_ca_topic_score_gemma":0.001476205,"domain_scores_codex":[0.9975982,0.001234096,0.0002796206,0.0002863859,0.0003665439,0.000235119],"domain_scores_gemma":[0.9952661,0.003508266,0.0003244561,0.0003050664,0.0002398933,0.0003562662],"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":[0.0007020365,0.0002811758,0.02873676,0.00042032,0.0002779027,0.06234384,0.002686635,0.0007417186,0.004048544,0.07093191,0.6890196,0.1398096],"study_design_scores_gemma":[0.0006179057,0.0003141662,0.009788863,0.0006793042,0.0002663544,0.05210439,0.002622354,0.00245239,0.002440336,0.222644,0.705924,0.0001459565],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.005508012,0.002738018,0.0005724972,0.9743695,0.01116859,0.00001298026,0.00004013581,0.00001643405,0.00557393],"genre_scores_gemma":[0.0887182,0.006064404,0.001569092,0.8147897,0.07779694,0.00006606124,0.00006401067,0.00004128802,0.01089024],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02002948,"threshold_uncertainty_score":0.01655269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0526189605392372,"score_gpt":0.2768528212190509,"score_spread":0.2242338606798137,"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."}}