{"id":"W2607388123","doi":"10.23889/ijpds.v1i1.47","title":"General Public Views on Uses and Users of Administrative Health Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Public health; Business; Public relations; Internet privacy; Information privacy; Agency (philosophy); Medicine; Political science; Nursing; Computer science; Sociology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.005253788,0.00009008501,0.0001749156,0.0002449997,0.003040792,0.0003043558,0.003482895,0.00004551929,0.00005468491],"category_scores_gemma":[0.005513588,0.00007343417,0.00001686559,0.00009009804,0.0002483506,0.004270106,0.0009063933,0.0002505138,0.000006006463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002317656,"about_ca_system_score_gemma":0.002437426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002901166,"about_ca_topic_score_gemma":0.001423169,"domain_scores_codex":[0.9977117,0.0001391552,0.0007384765,0.0003667373,0.0006707307,0.000373257],"domain_scores_gemma":[0.9959426,0.000249261,0.001563828,0.001255528,0.0006699759,0.0003187905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000172985,0.0002680224,0.4176112,0.0001452864,0.00007070164,0.000001388492,0.003241134,0.00002017986,0.0001476979,0.2066702,0.2443831,0.1272682],"study_design_scores_gemma":[0.0005795991,0.0001235034,0.6513909,0.0001785219,0.000004693198,0.00001241568,0.000846608,0.009025652,0.000003947797,0.001710168,0.3360254,0.00009854804],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7590224,0.00012607,0.003949203,0.2112232,0.01686618,0.001179312,0.005633017,0.00002788722,0.001972713],"genre_scores_gemma":[0.9872612,0.0003714146,0.005793132,0.003265279,0.00160839,0.00001315695,0.00122405,0.000009975669,0.0004533943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2337798,"threshold_uncertainty_score":0.9982571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7371393720034938,"score_gpt":0.6781846523944396,"score_spread":0.05895471960905418,"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."}}