{"id":"W6923384012","doi":"10.1371/journal.pone.0285659.s002","title":"COREQ checklist.","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Focus group; Key (lock); Qualitative research; Theme (computing); Mobile apps; Content analysis; Mobile device; Telemedicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01512937,0.001692775,0.002906605,0.005356926,0.002310485,0.003217994,0.004129526,0.002208972,0.3922143],"category_scores_gemma":[0.04421774,0.001783044,0.002221996,0.004276742,0.0008256331,0.003158915,0.004401212,0.003586256,0.09290709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003731579,"about_ca_system_score_gemma":0.01949878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01033325,"about_ca_topic_score_gemma":0.02096678,"domain_scores_codex":[0.991582,0.003320538,0.002096473,0.0006512981,0.001674238,0.0006754631],"domain_scores_gemma":[0.9779361,0.007646226,0.001187294,0.001217625,0.01129049,0.0007223453],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007082989,0.0005991321,0.003063202,0.009107732,0.00005980038,0.0002167137,0.002401634,0.0003980908,0.0002478161,0.004783497,0.8151979,0.1632162],"study_design_scores_gemma":[0.001152468,0.0004282564,0.01620318,0.009458743,0.00009090234,0.0003590125,0.005356578,0.0006993798,0.0003974998,0.01312043,0.9525814,0.000152162],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01433519,0.004572117,0.03166511,0.008921293,0.002286552,0.2111142,0.5562385,0.003276969,0.16759],"genre_scores_gemma":[0.01728873,0.004248232,0.07479825,0.005013939,0.000265394,0.6693295,0.1383981,0.001276518,0.08938139],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9848706,"threshold_uncertainty_score":0.8669326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1315616455130201,"score_gpt":0.3561856660315886,"score_spread":0.2246240205185685,"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."}}