{"id":"W3024348737","doi":"10.1016/j.sapharm.2020.04.022","title":"Development of an electronic tool (e-AdPharm) to address unmet needs and barriers of community pharmacists to provide medication adherence support to patients","year":2020,"lang":"en","type":"article","venue":"Research in Social and Administrative Pharmacy","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"AstraZeneca (Canada); Université de Montréal; Université Laval; The Quebec Population Health Research Network; Centre Hospitalier Universitaire de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal","funders":"Université de Montréal","keywords":"Focus group; Medicine; Medication adherence; Medical prescription; Thematic analysis; Pharmacy; Family medicine; Qualitative research; Nursing","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":[],"consensus_categories":[],"category_scores_codex":[0.001041813,0.0001234706,0.0002935196,0.0001335715,0.0001895406,0.00001449275,0.0002342423,0.00003111166,0.0002771094],"category_scores_gemma":[0.0004884723,0.0001191121,0.0000185003,0.000952912,0.0001846136,0.0001146252,0.0001546569,0.0004189874,0.00001800015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001012291,"about_ca_system_score_gemma":0.001658446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000622841,"about_ca_topic_score_gemma":0.00002662306,"domain_scores_codex":[0.9979578,0.000359825,0.0004387041,0.0002143335,0.0006831042,0.0003462038],"domain_scores_gemma":[0.9984137,0.00009812357,0.00008686299,0.0001076098,0.0003762316,0.0009174813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006924958,0.001614692,0.1318365,0.001691867,0.000169949,0.00001720496,0.1728939,8.153805e-7,0.1657172,0.001059924,0.008449548,0.5096234],"study_design_scores_gemma":[0.01404423,0.01072227,0.3540216,0.0006488911,0.00008315549,0.000009928775,0.03752235,0.0001703567,0.4766198,0.0006644803,0.1046384,0.0008545258],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927896,0.0000209946,0.00009350327,0.005110482,0.00001600043,0.001309315,0.00005807438,0.00001015883,0.0005918738],"genre_scores_gemma":[0.9973055,0.0000371565,0.0006091419,0.001649286,0.00004988696,0.000246318,0.00004322829,0.000007799127,0.00005165757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5087689,"threshold_uncertainty_score":0.4857252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3570682049126789,"score_gpt":0.527307746235172,"score_spread":0.170239541322493,"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."}}