{"id":"W2344988130","doi":"10.1007/s10549-016-3784-1","title":"Germline RECQL mutations in high risk Chinese breast cancer patients","year":2016,"lang":"en","type":"article","venue":"Breast Cancer Research and Treatment","topic":"DNA Repair Mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Public Health Ontario; Women's College Hospital","funders":"","keywords":"Breast cancer; Nonsense mutation; Germline mutation; Cancer; Mutation; Genetics; Biology; Cancer research; Oncology; Gene mutation; Genome instability; Internal medicine; Medicine; Gene; Missense mutation; DNA; DNA damage","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":[0.0001538023,0.0003267194,0.0003014495,0.001154763,0.0006804836,0.000435368,0.0002859639,0.000401868,0.003850682],"category_scores_gemma":[0.0006460192,0.0002725415,0.0003007694,0.001121694,0.0002967312,0.000223563,0.0002257467,0.0002789502,0.0003021588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004240986,"about_ca_system_score_gemma":0.0004658716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009341277,"about_ca_topic_score_gemma":0.005934418,"domain_scores_codex":[0.9998382,0.00001672687,0.00001779791,0.00004225844,0.00003040546,0.00005456011],"domain_scores_gemma":[0.9997485,0.00005360727,0.0000908928,0.00001636567,0.00002204886,0.00006854552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000474555,0.00006770826,0.984678,0.00002822487,0.00004581624,0.004705233,0.0004341405,0.00007798912,0.005344368,0.00009689377,0.0001999427,0.003847049],"study_design_scores_gemma":[0.00002055644,0.0001172299,0.9907046,0.000006951884,0.00009506581,0.006992741,0.0005720269,0.0001958766,0.0007370323,0.0001004453,0.00044692,0.00001044569],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992095,0.0001491897,0.0000200105,0.00003836534,0.0000033202,0.000003307584,0.00007327367,0.000003551713,0.000499412],"genre_scores_gemma":[0.999506,0.00007734941,0.00002207395,0.00001931293,0.000005181846,0.000002281727,0.00006804334,0.000001599977,0.0002982886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009341277,"threshold_uncertainty_score":0.01857382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360487008653274,"score_gpt":0.3217027717941388,"score_spread":0.3080979017076061,"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."}}