{"id":"W4238999462","doi":"10.32920/ryerson.14648532.v1","title":"The points paradigm 40 years later : an examination of Canada's immigration point system","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Point (geometry); Point system; Context (archaeology); Selection (genetic algorithm); Computer science; Operations research; Risk analysis (engineering); Data science; Political science; History; Business; Economics; Engineering; Artificial intelligence; Mathematical economics; Law; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003083714,0.0001827605,0.0002699281,0.003657569,0.02126203,0.006809073,0.001403875,0.0009288387,0.005427265],"category_scores_gemma":[0.005881425,0.0001895975,0.0003101761,0.006976172,0.005173351,0.002108118,0.002779147,0.002380668,0.0003657307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09750007,"about_ca_system_score_gemma":0.1002603,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9858214,"about_ca_topic_score_gemma":0.9940705,"domain_scores_codex":[0.9968203,0.0005669863,0.00006472405,0.0002384684,0.001276082,0.001033308],"domain_scores_gemma":[0.9957935,0.0004575473,0.0002817595,0.0001673286,0.002300249,0.0009996744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002029843,0.0001514706,0.1282929,0.0001996434,0.00004447688,0.002602361,0.3149524,0.001228738,0.001669379,0.3853444,0.03044811,0.1348632],"study_design_scores_gemma":[0.00003464966,0.000108023,0.2185461,0.0003318378,0.0000496208,0.0004392574,0.3385857,0.002224494,0.0008029101,0.007559028,0.4312093,0.0001091047],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.785828,0.001169972,0.001441726,0.008389497,0.0001606856,0.0001680149,0.0007212953,0.00003051794,0.2020903],"genre_scores_gemma":[0.9678331,0.0007905376,0.001405401,0.0007779141,0.00001844691,0.00003136932,0.0002481487,0.00003106909,0.02886393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09750007,"threshold_uncertainty_score":0.7074158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02822329276749071,"score_gpt":0.1884656377510611,"score_spread":0.1602423449835703,"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."}}