{"id":"W3005236094","doi":"10.12927/hcpol.2019.26072","title":"Envisioning Implementation of a Personalized Approach in Breast Cancer Screening Programs: Stakeholder Perspectives","year":2019,"lang":"en","type":"article","venue":"Healthcare policy","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; McGill Genome Centre","funders":"Government of Canada; Canadian Institutes of Health Research; Fondation du cancer du sein du Québec; Genome Canada","keywords":"Personalized medicine; Stakeholder; Breast cancer; Personalization; Health care; Perspective (graphical); Computer science; Knowledge management; Medicine; Cancer; Bioinformatics; Public relations; World Wide Web; Political science; Artificial intelligence; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.03729041,0.0005016073,0.0002693389,0.0009424512,0.01712592,0.0104878,0.002518506,0.005863278,0.003514322],"category_scores_gemma":[0.02164214,0.0004423981,0.0006101101,0.0007414024,0.01110673,0.003909952,0.006425852,0.0039519,0.0002470807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03229802,"about_ca_system_score_gemma":0.05404746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.216325,"about_ca_topic_score_gemma":0.2548039,"domain_scores_codex":[0.9542644,0.03497443,0.000593623,0.0009393484,0.002606605,0.006621579],"domain_scores_gemma":[0.9728469,0.01251178,0.001672442,0.0005144433,0.005351921,0.007102575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001565977,0.0006237385,0.07292507,0.0003808133,0.00009555302,0.005233058,0.7160271,0.005862156,0.004399931,0.152023,0.009921337,0.03235162],"study_design_scores_gemma":[0.00004785597,0.0002165242,0.009337333,0.0004981217,0.00004673611,0.0004921283,0.8878901,0.005466934,0.000883183,0.02702217,0.06799833,0.0001005152],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6976331,0.0007883667,0.02688419,0.1652285,0.0001554675,0.0007957242,0.0001312293,0.00005994578,0.1083235],"genre_scores_gemma":[0.9916111,0.0001985071,0.003924385,0.002815133,0.00001349819,0.00009224548,0.00002287062,0.000007726087,0.001314551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.216325,"threshold_uncertainty_score":0.4301318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04287899452116898,"score_gpt":0.375469362444673,"score_spread":0.332590367923504,"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."}}