{"id":"W6977474350","doi":"10.6084/m9.figshare.c.3605423_d1.v1","title":"Additional file 1: Table S1. of Describing the linkages of the immigration, refugees and citizenship Canada permanent resident data and vital statistics death registry to Ontarioâ s administrative health database","year":2016,"lang":"en","type":"article","venue":"Figshare","topic":"Archaeology and Cultural Heritage","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Refugee; Citizenship; Matching (statistics); Health statistics; Process (computing); Cover (algebra); Confidentiality","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009545679,0.00006127297,0.00008817136,0.000006279988,0.0004781829,0.00001126583,0.0002723435,0.00002834466,0.1757327],"category_scores_gemma":[0.00254671,0.0000328987,0.000007209527,0.0000542936,0.0001226213,0.00009341999,0.0002577385,0.00007325975,0.000003700386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005617567,"about_ca_system_score_gemma":0.001375991,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09833314,"about_ca_topic_score_gemma":0.9022766,"domain_scores_codex":[0.9992127,0.0001358115,0.0001462219,0.0001557597,0.0002148092,0.0001346893],"domain_scores_gemma":[0.9984081,0.001039433,0.0001467321,0.0002254373,0.0001039342,0.00007632242],"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":[0.000004384893,0.000002892679,0.0002861326,0.00002272614,0.000008005105,0.000002637484,0.002335526,1.026545e-7,0.00000896422,0.0006541669,0.9964543,0.0002201841],"study_design_scores_gemma":[0.0001416509,0.00009244293,0.0841608,0.002581417,0.00001175056,0.00001048197,0.01312765,0.000008498526,0.0001676306,0.0006325007,0.898908,0.0001571714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.004280305,0.000119788,0.000002522181,0.002764219,0.00001419303,0.000172453,0.9924077,0.000003424306,0.0002353763],"genre_scores_gemma":[0.5457621,0.00002355623,0.0007901152,0.0004628805,0.00008880339,0.00007949462,0.4495586,0.000005790794,0.00322873],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.8039435,"threshold_uncertainty_score":0.9076712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1208755225101863,"score_gpt":0.3207329985456625,"score_spread":0.1998574760354762,"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."}}