{"id":"W6906459586","doi":"10.17605/osf.io/ubzn2","title":"Canadian data source identification and evaluation datasets","year":2022,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Data source; Data collection; Health data; Information source (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.03176677,0.0001354116,0.0001950012,0.0002282196,0.002548276,0.00004074918,0.001077192,0.0001367397,0.5001131],"category_scores_gemma":[0.006399731,0.0001575795,0.00002118513,0.000231489,0.00005263428,0.0004427909,0.002338136,0.001009089,0.3335107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001088891,"about_ca_system_score_gemma":0.00178711,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05187204,"about_ca_topic_score_gemma":0.02143408,"domain_scores_codex":[0.994315,0.002453865,0.000838969,0.001117159,0.0007795093,0.0004955023],"domain_scores_gemma":[0.9945541,0.0006215128,0.0004111413,0.003756485,0.0001497948,0.0005069444],"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":[0.00007601373,0.00007530684,0.04219789,0.0003884943,0.0000430259,0.000003092888,0.008423685,0.0008861898,0.0001662517,0.001289199,0.8019106,0.1445403],"study_design_scores_gemma":[0.0005676287,7.769852e-7,0.0398962,0.00004136034,0.00005012856,0.000008767952,0.001843461,0.06028542,0.00001197503,0.001083066,0.8960513,0.0001598808],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3001252,0.00001595241,0.006222524,0.01856072,0.002948852,0.007550365,0.002948041,0.0003542546,0.6612741],"genre_scores_gemma":[0.8961101,0.00008886593,0.0003628074,0.003204344,0.0001915715,0.001244117,0.009343732,0.00003375964,0.0894207],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5959849,"threshold_uncertainty_score":0.9987503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1907930457884911,"score_gpt":0.4399698774696582,"score_spread":0.2491768316811671,"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."}}