{"id":"W6904637224","doi":"10.1371/journal.pone.0281733.s001","title":"COREQ.","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Primary care; Citizen journalism; Health care; Ethnography; Big data; Primary health care; Indigenous; Space (punctuation); Participatory evaluation","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"],"consensus_categories":[],"category_scores_codex":[0.005150025,0.001310671,0.001710162,0.005256208,0.003200647,0.00899588,0.004190496,0.003870235,0.8741514],"category_scores_gemma":[0.03111334,0.001088292,0.001313825,0.007176474,0.001212642,0.006508773,0.007313224,0.002834001,0.7514738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005528389,"about_ca_system_score_gemma":0.01236053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02137345,"about_ca_topic_score_gemma":0.02061422,"domain_scores_codex":[0.9955764,0.001193494,0.0004008413,0.0005931828,0.001539928,0.0006962731],"domain_scores_gemma":[0.9867079,0.002896409,0.0004730902,0.001251307,0.006830457,0.001840782],"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":[0.00008499535,0.00004107552,0.0003355846,0.000976546,0.000007970593,0.00002696955,0.0002418041,0.00003848354,0.00005482005,0.005005216,0.9338165,0.05936996],"study_design_scores_gemma":[0.00004470674,0.00001976975,0.001136097,0.0007413645,0.000006838455,0.00005117213,0.0003483334,0.00004813687,0.00006337515,0.00362341,0.9939013,0.00001546263],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.0008807601,0.002923215,0.003693974,0.011094,0.003060768,0.002030999,0.265909,0.004611052,0.7057962],"genre_scores_gemma":[0.01333272,0.00622708,0.009810802,0.01655935,0.001362556,0.009110085,0.1717106,0.008347954,0.7635388],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.99485,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5495761821669375,"score_gpt":0.5043685541761046,"score_spread":0.04520762799083289,"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."}}