{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001706718,0.0001193703,0.0001551443,0.0001459697,0.00004191519,0.0000129573,0.0001076409,0.00008946595,0.00006207828],"category_scores_gemma":[0.000007691868,0.0001226606,0.00005684145,0.0002966056,0.00005958143,0.000007571022,0.00005413302,0.00009690085,0.000001509804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002046057,"about_ca_system_score_gemma":0.0007426609,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008644531,"about_ca_topic_score_gemma":0.00055863,"domain_scores_codex":[0.9988791,0.00009438932,0.000239296,0.000344425,0.0001626284,0.0002801994],"domain_scores_gemma":[0.9994451,0.000005953919,0.0001263505,0.0002203824,0.0001446024,0.00005755938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002366071,0.0001610001,0.7712419,0.0004187717,0.0001224384,7.780374e-7,0.01810602,0.0005648136,0.03630359,0.003500156,0.0002515633,0.1690924],"study_design_scores_gemma":[0.004937487,0.0004556746,0.8489779,0.0002659598,0.00002521803,0.00006002374,0.1284684,0.0005081328,0.009673503,0.0001436241,0.005837183,0.0006468363],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918979,0.002526047,0.0003877986,0.004170973,0.00003948882,0.000583896,0.0001506472,0.00001016317,0.0002330169],"genre_scores_gemma":[0.9957744,0.0003532215,0.002954079,0.0002880028,0.0002055891,0.000157973,0.0001396105,0.00002575643,0.0001013027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1684455,"threshold_uncertainty_score":0.997957,"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."}}