{"id":"W2972807366","doi":"10.1177/1833358319873968","title":"Protection of digital health information: Examining guidance from the physician regulatory colleges in Canada","year":2019,"lang":"en","type":"article","venue":"Health Information Management Journal","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Scope (computer science); Incentive; Business; Information and Communications Technology; Public relations; Thematic analysis; Corporate governance; Service (business); Political science; Marketing; Computer science; Qualitative research; Sociology; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004362527,0.0001862936,0.0004109933,0.0002903339,0.0009792298,0.0001083908,0.0003780419,0.00006994844,0.0002613665],"category_scores_gemma":[0.0001291158,0.0001428418,0.00004392245,0.0006766595,0.00002664003,0.009356008,0.0001234136,0.0009354352,0.0002292322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002831181,"about_ca_system_score_gemma":0.005273867,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1173497,"about_ca_topic_score_gemma":0.03117158,"domain_scores_codex":[0.9932405,0.0005415402,0.004571799,0.0001040043,0.0008970329,0.0006451188],"domain_scores_gemma":[0.9941683,0.0002122151,0.004562785,0.0004427555,0.0003870169,0.0002268633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003579588,0.00005103063,0.3232039,0.006809223,0.0000622947,5.086156e-7,0.03516301,0.002657653,3.355871e-7,0.006157137,0.07832595,0.5472111],"study_design_scores_gemma":[0.001665841,0.00009622167,0.5965899,0.001233598,0.000002192575,0.000001759662,0.03772575,0.005835568,8.293376e-7,0.0004036936,0.3563064,0.0001382697],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8290752,0.0006180295,0.03141288,0.04623909,0.007532225,0.01536067,0.0009286463,0.0001753603,0.06865785],"genre_scores_gemma":[0.9481216,0.0002095452,0.00108605,0.04992583,0.0001611219,0.0001300059,0.0002421922,0.000009298654,0.0001143674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5470728,"threshold_uncertainty_score":0.986507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03942176412685695,"score_gpt":0.3447569162764054,"score_spread":0.3053351521495484,"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."}}