{"id":"W3214988070","doi":"10.2196/33962","title":"Authors' Responses to Peer Review of “Machine Learning and Medication Adherence: Scoping Review”","year":2021,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Peer review; Medicine; Psychology; Computer science; Medical education; Chemistry","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.113073,0.002165521,0.00598198,0.01238591,0.006721353,0.01069632,0.004948002,0.02310745,0.04766724],"category_scores_gemma":[0.5888448,0.001997658,0.006725961,0.009261645,0.004152083,0.007633644,0.01171067,0.01320951,0.023645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01291324,"about_ca_system_score_gemma":0.04515625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007280112,"about_ca_topic_score_gemma":0.01275476,"domain_scores_codex":[0.7696455,0.07095356,0.06481575,0.006929968,0.08095623,0.006699006],"domain_scores_gemma":[0.2901011,0.1389881,0.04790886,0.01346103,0.500245,0.009295921],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008913569,0.00001460155,0.0002375771,0.0100752,0.0001071743,0.000154294,0.0008186094,0.00004072827,0.0001954841,0.0006123008,0.9727197,0.01493514],"study_design_scores_gemma":[0.0001758642,0.00004402619,0.0009562614,0.03159501,0.0002110005,0.0002577318,0.001376947,0.0002089597,0.0003287773,0.001447091,0.9632636,0.0001347559],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0007677468,0.0148326,0.002491531,0.5997903,0.366134,0.003794596,0.004415374,0.0004868535,0.007286882],"genre_scores_gemma":[0.02095186,0.04772685,0.0149973,0.6611391,0.1564511,0.02864517,0.008975879,0.001725568,0.0593872],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.886927,"threshold_uncertainty_score":0.5979943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08921805395141796,"score_gpt":0.4431000275364309,"score_spread":0.3538819735850129,"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."}}