{"id":"W2913263577","doi":"10.2196/12561","title":"Medication Adherence Prediction Through Online Social Forums: A Case Study of Fibromyalgia","year":2019,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Machine learning; Computer science; Random forest; Artificial intelligence; Big data; Transfer of learning; Fibromyalgia; Pharmacy; Medical prescription; Medical record; Scalability; Data science; Medicine; Family medicine; Data mining; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002958498,0.0004212268,0.0003889758,0.00113522,0.002117852,0.000999998,0.000904595,0.001888367,0.001713652],"category_scores_gemma":[0.01368289,0.000231819,0.0005721325,0.00142474,0.000619304,0.001486915,0.0009019601,0.001588974,0.0002860691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009743742,"about_ca_system_score_gemma":0.0007761054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01386002,"about_ca_topic_score_gemma":0.02518906,"domain_scores_codex":[0.9979628,0.001328752,0.0001099198,0.0001433896,0.0002789571,0.000176108],"domain_scores_gemma":[0.9861237,0.01076108,0.00120772,0.0004943867,0.0005309205,0.0008822688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006629818,0.00723701,0.758399,0.000597178,0.0003100383,0.03618233,0.03618849,0.00940766,0.001652035,0.003436567,0.01124159,0.1346852],"study_design_scores_gemma":[0.0005061618,0.003607495,0.6121897,0.0006388172,0.0003544378,0.02900136,0.1137037,0.1931206,0.004113545,0.00964865,0.03284323,0.0002722036],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943461,0.0002010819,0.001590797,0.002065079,0.00001459505,0.00008447213,0.0003730275,0.00003184944,0.001293105],"genre_scores_gemma":[0.9935375,0.0003183269,0.004568967,0.0003117772,0.00004565129,0.00007860831,0.0003344454,0.00001265231,0.000792154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01386002,"threshold_uncertainty_score":0.02755868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05093811549338431,"score_gpt":0.3701887345469517,"score_spread":0.3192506190535673,"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."}}