{"id":"W3104118410","doi":"10.22541/au.160391056.64115187/v1","title":"FAIR Access to Personal Health Information in Private and Public COVID-19 Health Applications","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital","funders":"","keywords":"eHealth; Internet privacy; Coronavirus disease 2019 (COVID-19); Business; Pandemic; Corporate governance; Personally identifiable information; Public health; Tracking (education); Health care; Public relations; Computer security; Computer science; Medicine; Psychology; Political science; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005679547,0.0002453616,0.0006378113,0.0004281848,0.0001050902,0.0002178297,0.0003454829,0.0001069303,0.0001471751],"category_scores_gemma":[0.000461017,0.0002406847,0.00005863326,0.0005121017,0.00005053251,0.0003969439,0.001183282,0.0005095412,0.00009807832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009734051,"about_ca_system_score_gemma":0.005028728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002012192,"about_ca_topic_score_gemma":0.001204954,"domain_scores_codex":[0.9978092,0.0001203049,0.0007239135,0.0005340435,0.0004164673,0.0003960996],"domain_scores_gemma":[0.9969894,0.00005885386,0.0003521766,0.0005519501,0.00009725279,0.001950369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005420702,0.0006090358,0.3415993,0.02998559,0.0002233653,0.0000148455,0.008435068,0.0003234071,0.000006400871,0.0125394,0.3563155,0.2494061],"study_design_scores_gemma":[0.001482346,0.0001400011,0.2736246,0.0001995168,0.000009077014,0.00001370252,0.0005382004,0.002626402,0.00000101146,0.000724306,0.720306,0.0003347936],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01369424,0.0007191031,0.2035358,0.7633027,0.0001458197,0.01237157,0.003728716,0.000776226,0.001725825],"genre_scores_gemma":[0.7118151,0.0009302901,0.007347598,0.2629243,0.0001857617,0.002464831,0.01424044,0.00003688308,0.00005469974],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.6981209,"threshold_uncertainty_score":0.9814837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08467306100200275,"score_gpt":0.4024963679076321,"score_spread":0.3178233069056293,"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."}}