{"id":"W38144905","doi":"10.1093/beheco/arad103","title":"2010年度日本乳癌学会班研究課題最終報告「我が国における遺伝性乳癌・卵巣癌(BRCA陽性患者)及び未発症陽性者のデータベース構築及び対策に関する研究」","year":2012,"lang":"en","type":"article","venue":"日本乳癌学会学術総会プログラム・抄録集","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001854085,0.0003185901,0.0002816799,0.0008967659,0.0004932226,0.001247531,0.00045535,0.0004539002,0.005577442],"category_scores_gemma":[0.00141001,0.0003532392,0.0003656819,0.0005555212,0.0008447015,0.0007280636,0.000415855,0.0005930365,0.002190529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001693189,"about_ca_system_score_gemma":0.0008255592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01392734,"about_ca_topic_score_gemma":0.02108666,"domain_scores_codex":[0.9994478,0.0001163802,0.00003206011,0.0002206394,0.000126887,0.00005631928],"domain_scores_gemma":[0.9987363,0.0002681708,0.0004458124,0.0001246727,0.0002952843,0.0001298192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001288857,0.0002714936,0.6017205,0.0004415257,0.0006790549,0.000913852,0.001591001,0.004282221,0.05956833,0.00732711,0.009019972,0.3128961],"study_design_scores_gemma":[0.0000364911,0.0005366718,0.885287,0.0001541176,0.0004193007,0.003251773,0.0005276133,0.009596379,0.02440352,0.003715962,0.07197284,0.00009846727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9520977,0.006033511,0.01576395,0.001098967,0.0002563246,0.00007233359,0.004529922,0.0004237541,0.01972356],"genre_scores_gemma":[0.9762947,0.002188022,0.008611633,0.0003630077,0.0001477323,0.0000473877,0.002966434,0.00006594307,0.009315228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01392734,"threshold_uncertainty_score":0.02769256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03299318981544413,"score_gpt":0.2294138231443669,"score_spread":0.1964206333289228,"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."}}