{"id":"W6894324064","doi":"10.5683/sp3/anaaaj","title":"Immigration Statistics in the Sessional Papers 1883-1894","year":2015,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Parliament; Immigration; Listing (finance); Official statistics; The Internet; Statistical analysis; Deportation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001274428,0.001539988,0.001433838,0.006452973,0.001202669,0.002917134,0.001871141,0.000937838,0.05431084],"category_scores_gemma":[0.008352866,0.000844327,0.0009106853,0.01481597,0.0003707535,0.001061816,0.001804293,0.001780643,0.08022157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003255736,"about_ca_system_score_gemma":0.007295998,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2603308,"about_ca_topic_score_gemma":0.3412305,"domain_scores_codex":[0.9979858,0.0001799123,0.0002826853,0.00041348,0.0007503053,0.0003877002],"domain_scores_gemma":[0.9962792,0.000485981,0.000668078,0.0005602778,0.001628299,0.0003782155],"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":[0.00002569671,0.000006175238,0.001269229,0.0001219586,0.00001421662,0.00001055789,0.00002061704,0.00007267357,0.00002346503,0.0003602021,0.9968803,0.001195034],"study_design_scores_gemma":[0.00007637699,0.000008870855,0.02042994,0.0002008812,0.00002045006,0.00003449373,0.0001249892,0.0001166216,0.0001365968,0.0002980142,0.9785308,0.00002198621],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002061919,0.00005787394,0.00002198957,0.00004632941,0.00004457942,0.000005075038,0.9980382,0.0001094955,0.001470159],"genre_scores_gemma":[0.0006871933,0.00005394004,0.00007645427,0.00002838967,0.00001653178,0.00003156477,0.9968153,0.00005554835,0.002235156],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7396692,"threshold_uncertainty_score":0.5176311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02440812140746459,"score_gpt":0.3043024785822963,"score_spread":0.2798943571748317,"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."}}