{"id":"W2755756708","doi":"10.1109/ichi.2017.96","title":"Computable Adherence","year":2017,"lang":"en","type":"article","venue":"","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Victoria","funders":"","keywords":"Soundness; Confusion; Formalism (music); Computer science; Informatics; Medication adherence; Health informatics; Medicine; Psychology; Nursing; Engineering; Programming language","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00005024764,0.00003645673,0.00008115697,0.000008967143,0.00013518,0.00002956739,0.0001362986,0.00001973336,0.006675752],"category_scores_gemma":[0.00006577581,0.00002744101,0.00001930938,0.00001322075,0.00005832577,0.00006155732,0.00002984416,0.00005242302,0.006901679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000560678,"about_ca_system_score_gemma":0.00004859355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004906672,"about_ca_topic_score_gemma":0.000001370899,"domain_scores_codex":[0.9996442,0.000002625437,0.0000669814,0.00009686287,0.0001038062,0.00008553734],"domain_scores_gemma":[0.9993253,0.000006666431,0.00004647419,0.0004889019,0.00004479188,0.00008781048],"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":[0.00006165967,0.0002250667,0.3362015,0.00009164566,0.00004073412,0.00005658044,0.00005906248,0.00000124678,0.004551566,0.02708115,0.4594667,0.172163],"study_design_scores_gemma":[0.001816791,0.0002687676,0.6949573,0.0002042907,0.00002474804,0.00008013089,0.00008329863,0.003967389,0.005900753,0.002427049,0.2900994,0.0001701099],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09548171,0.00005038228,0.004705428,0.004007251,0.0001608013,0.0001239006,3.394426e-7,0.00006174974,0.8954085],"genre_scores_gemma":[0.8552296,0.00001359855,0.002914266,0.001195046,0.00006263389,0.000007013349,0.000001304854,0.000002447004,0.1405741],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7597479,"threshold_uncertainty_score":0.9942323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1130635679406081,"score_gpt":0.3934294013270221,"score_spread":0.280365833386414,"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."}}