{"id":"W6925345339","doi":"10.17863/cam.70941","title":"Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation (PERSPECTIVE I)","year":2021,"lang":"en","type":"other","venue":"Apollo (University of Cambridge)","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre Hospitalier Universitaire de Québec; University of Toronto; McGill University; Génome Québec; Genome Canada; Université Laval","keywords":"Breast cancer; Risk assessment; Context (archaeology); Breast cancer screening; Identification (biology); Cancer screening; Health care; Perspective (graphical)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0137802,0.0005543642,0.0003905703,0.0009074178,0.002524763,0.00621879,0.002402733,0.007016568,0.009416708],"category_scores_gemma":[0.02649602,0.0002579056,0.001152608,0.0009293942,0.00554368,0.002849469,0.004131218,0.006710722,0.001703018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02165146,"about_ca_system_score_gemma":0.09582968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4850943,"about_ca_topic_score_gemma":0.612675,"domain_scores_codex":[0.9837528,0.007630004,0.0005265417,0.0007913232,0.005817116,0.001482225],"domain_scores_gemma":[0.982139,0.006347884,0.000750397,0.000886252,0.007931681,0.001944786],"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":[0.00006241245,0.0001130102,0.002801547,0.001508087,0.00004898828,0.0003812195,0.004092813,0.001294171,0.0004503229,0.3170623,0.424464,0.2477211],"study_design_scores_gemma":[0.00002355045,0.00004916173,0.002733279,0.002091683,0.00004822557,0.0001822533,0.001547463,0.0004134073,0.0004126819,0.03023011,0.9622263,0.0000419773],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.001591435,0.0152558,0.008600976,0.7996833,0.004477183,0.0002088094,0.0003795187,0.0001105343,0.1696924],"genre_scores_gemma":[0.1070751,0.06525566,0.03935615,0.6804934,0.007841188,0.0007961035,0.0007875832,0.0002286145,0.09816637],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4850943,"threshold_uncertainty_score":0.9645415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00713152976432759,"score_gpt":0.2355669511650834,"score_spread":0.2284354214007558,"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."}}