{"id":"W4380149964","doi":"10.1016/j.jval.2023.03.2074","title":"RWD44 Use of Real-World Data for Hard-to-Identify Patient Population: Methodology and a Case Study","year":2023,"lang":"en","type":"article","venue":"Value in Health","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"EVERSANA (Canada)","funders":"","keywords":"Real world data; Real world evidence; Medicine; Matching (statistics); Psychological intervention; Computer science; Intensive care medicine; Data science; Internal medicine; Psychiatry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04553628,0.0006031941,0.0006066762,0.003252502,0.001823351,0.002763393,0.002436723,0.002507963,0.004292734],"category_scores_gemma":[0.1186158,0.0007536932,0.001205078,0.003157144,0.001732856,0.001769098,0.003253835,0.001295998,0.001085194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002252544,"about_ca_system_score_gemma":0.006121911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008585314,"about_ca_topic_score_gemma":0.01072304,"domain_scores_codex":[0.9362944,0.05027074,0.004641172,0.002400657,0.005429693,0.0009633102],"domain_scores_gemma":[0.8780797,0.08830135,0.006456136,0.01374187,0.01216136,0.001259561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003559154,0.01050156,0.5676605,0.004755427,0.001040576,0.01096276,0.04875028,0.005739512,0.006467851,0.01559094,0.01317697,0.3117944],"study_design_scores_gemma":[0.004253792,0.01929321,0.4302642,0.01054143,0.003054927,0.03366561,0.1194316,0.06726044,0.05655042,0.02230449,0.2321283,0.001251482],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8351628,0.001449469,0.119769,0.003513846,0.0001933564,0.01809289,0.005639305,0.0002827851,0.01589666],"genre_scores_gemma":[0.8148197,0.001094901,0.1614024,0.001264435,0.0000816063,0.01628553,0.00225371,0.0001429467,0.002654654],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04553628,"threshold_uncertainty_score":0.2408217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8950720303877125,"score_gpt":0.6683719799046978,"score_spread":0.2267000504830148,"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."}}