{"id":"W6945311443","doi":"10.25318/9810039601-fra","title":"Lieu des études comparé au lieu de résidence, selon le plus haut niveau de scolarité : Canada, provinces et territoires, divisions de recensement et subdivisions de recensement","year":2023,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Population; China","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":["metaepi_narrow","sts"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.00457282,0.001775185,0.001529286,0.000822945,0.003295266,0.0008954676,0.00191951,0.0006831408,0.000141936],"category_scores_gemma":[0.007343825,0.002198846,0.0001519898,0.001726146,0.0007506831,0.0005435018,0.0008697054,0.00209617,0.00007509381],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.06984761,"about_ca_system_score_gemma":0.1220628,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9991158,"about_ca_topic_score_gemma":0.9999853,"domain_scores_codex":[0.9854286,0.002891996,0.002239983,0.001895263,0.003723721,0.003820437],"domain_scores_gemma":[0.987626,0.00552001,0.001736959,0.00147536,0.001371655,0.002270042],"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":[0.0001563691,0.0006668573,0.005983205,0.001725037,0.0005675374,0.002186749,0.002149016,0.008462669,0.0007381776,0.01059048,0.9631677,0.003606192],"study_design_scores_gemma":[0.001374985,0.0004606278,0.2960086,0.008840645,0.001468604,0.0002148727,0.006978313,0.01986831,0.000964101,0.002726452,0.6579948,0.003099706],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01337064,0.0009464427,0.01350306,0.00498043,0.001306001,0.002430406,0.9631399,0.0001919677,0.0001311719],"genre_scores_gemma":[0.08210845,0.002925622,0.02890003,0.0009041202,0.0002291405,0.0007759569,0.8818235,0.0005275469,0.001805643],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3051729,"threshold_uncertainty_score":0.9994994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833404738143032,"score_gpt":0.2998843804224205,"score_spread":0.2815503330409902,"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."}}