{"id":"W4396579378","doi":"10.2196/56493","title":"Individual-Level Digital Determinants of Health and Technology Acceptance of Patient Portals: Cross-Sectional Assessment","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Noaber Foundation","keywords":"Cross-sectional study; Environmental health; Computer science; Medicine; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004528113,0.0001486056,0.0004945048,0.000901922,0.0005553,0.00003903062,0.0002703283,0.0002706454,0.0001190618],"category_scores_gemma":[0.0002998992,0.0001210487,0.00004874037,0.001177728,0.0004398426,0.0005508631,0.0004133169,0.00156474,0.00004350849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005937341,"about_ca_system_score_gemma":0.005078754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001260748,"about_ca_topic_score_gemma":0.00007772616,"domain_scores_codex":[0.9950254,0.0008002544,0.001710214,0.0003299695,0.001109578,0.001024602],"domain_scores_gemma":[0.9971068,0.001123308,0.0005063349,0.0003009721,0.0007698447,0.0001927312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003202811,0.0001440826,0.8906529,0.005888033,0.00005039256,0.000003825875,0.0125927,3.220385e-7,0.0000460944,0.00445147,0.002146432,0.08399173],"study_design_scores_gemma":[0.0009163541,0.003804526,0.9520134,0.003093685,0.000002357664,0.000043453,0.02493734,0.0007123107,0.0003930097,0.004618831,0.00923593,0.0002287961],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924522,0.001977134,0.0001228817,0.0003734857,0.0003859953,0.001849436,0.0005077079,0.00005751649,0.002273625],"genre_scores_gemma":[0.9985262,0.0001633074,0.0001114426,0.00002546844,0.00004656253,0.0006984941,0.00003504518,0.00002471362,0.0003687684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08376294,"threshold_uncertainty_score":0.9009492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2084257421268928,"score_gpt":0.5859313658994788,"score_spread":0.377505623772586,"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."}}