{"id":"W4394985843","doi":"10.2196/51350","title":"How to Elucidate Consent-Free Research Use of Medical Data: A Case for “Health Data Literacy”","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Health literacy; Computer science; Internet privacy; Data science; Health data; Medicine; Medical education; Health care; World Wide Web; Political science","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","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.5761122,0.001027867,0.002019122,0.003875634,0.009087588,0.02295632,0.007439748,0.04277661,0.003501879],"category_scores_gemma":[0.5778644,0.0016303,0.002890004,0.002655729,0.166824,0.05056485,0.02289256,0.04345934,0.001573038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01012695,"about_ca_system_score_gemma":0.04605567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003360965,"about_ca_topic_score_gemma":0.001919937,"domain_scores_codex":[0.3806792,0.5480528,0.02625832,0.01307405,0.0253968,0.006538868],"domain_scores_gemma":[0.1688486,0.7457202,0.01594216,0.04792434,0.0171975,0.004367221],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005962337,0.00004261452,0.0008961508,0.000695775,0.00005216069,0.0007462662,0.02638596,0.0002384134,0.0002208695,0.9373555,0.01060831,0.0226984],"study_design_scores_gemma":[0.000077809,0.00005434151,0.0003390232,0.003323357,0.00004386024,0.001239555,0.00602517,0.0007357979,0.0005988953,0.8876143,0.09986686,0.00008098421],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004948327,0.005827772,0.08643351,0.8772552,0.002095659,0.0005598683,0.00008851774,0.00008322517,0.02270794],"genre_scores_gemma":[0.3984096,0.007707578,0.1631782,0.4132847,0.005803743,0.005365177,0.0002247901,0.0002715614,0.005754617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9572234,"threshold_uncertainty_score":0.5227292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8268794793439164,"score_gpt":0.710600476082001,"score_spread":0.1162790032619153,"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."}}