{"id":"W2897929033","doi":"10.1177/2042098618804490","title":"Deprescribing conversations: a closer look at prescriber–patient communication","year":2018,"lang":"en","type":"article","venue":"Therapeutic Advances in Drug Safety","topic":"Patient-Provider Communication in Healthcare","field":"Health Professions","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bruyère; University of Ottawa; University of Waterloo; Centre Integre de Sante et de Services Sociaux de Laval; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Deprescribing; Medicine; Conversation; Thematic analysis; Health care; Action (physics); Family medicine; Nursing; Qualitative research; Psychology; Polypharmacy; Internal medicine; Communication","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0006377779,0.0002792475,0.0003729533,0.0001849369,0.001853557,0.000009888631,0.000898691,0.0001852118,0.0008061655],"category_scores_gemma":[0.0002660793,0.0002744049,0.00006987996,0.0004853005,0.0005131433,0.0007427352,0.000801498,0.0008523173,0.0006576139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001324704,"about_ca_system_score_gemma":0.0002730551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006431329,"about_ca_topic_score_gemma":0.005528039,"domain_scores_codex":[0.9942937,0.002795147,0.001310033,0.0004737673,0.0004102668,0.0007170578],"domain_scores_gemma":[0.9944202,0.002118445,0.0006508176,0.002188369,0.0004795039,0.0001426728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003907268,0.000675445,0.2430862,0.0009067956,0.0001568743,0.000004382209,0.4343498,0.0006907344,0.0005510572,0.07062665,0.003722974,0.2413218],"study_design_scores_gemma":[0.003833542,0.0001908122,0.01738411,0.001513807,0.00004778977,0.000004390603,0.05298017,0.003687751,0.000628906,0.0300833,0.8888787,0.0007666945],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4113495,0.2319214,0.005590515,0.02845002,0.006360808,0.01780988,0.0003028722,0.001842441,0.2963726],"genre_scores_gemma":[0.984631,0.005175062,0.003988501,0.004254822,0.0001217113,0.00071259,0.0001038264,0.00005827546,0.0009541824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8851557,"threshold_uncertainty_score":0.9999708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0979747242222918,"score_gpt":0.3990011828173144,"score_spread":0.3010264585950226,"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."}}