{"id":"W6888960853","doi":"10.25318/9810056101-fra","title":"Indicateurs de la qualité des données du questionnaire détaillé pour l'immigration, le lieu de naissance et la citoyenneté : Canada, provinces et territoires, régions métropolitaines de recensement, agglomérations 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; Census; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005454575,0.002007054,0.00169186,0.006726885,0.001817082,0.003671977,0.003131967,0.002050344,0.05831693],"category_scores_gemma":[0.05218623,0.001017809,0.001704642,0.01741307,0.0007000417,0.001538395,0.002063608,0.002651604,0.03051052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02325375,"about_ca_system_score_gemma":0.05305209,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9364405,"about_ca_topic_score_gemma":0.9448114,"domain_scores_codex":[0.9921727,0.0009825113,0.001228035,0.001218468,0.003079215,0.001319022],"domain_scores_gemma":[0.9548142,0.009743757,0.002305396,0.002799259,0.02848844,0.001848927],"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":[0.0000679597,0.00001881952,0.00458407,0.0005289399,0.00003824801,0.00001050334,0.00007946666,0.0001947618,0.00003185957,0.0003318021,0.9915834,0.002530213],"study_design_scores_gemma":[0.000539598,0.00002737493,0.1322386,0.001405183,0.0001082604,0.00004820301,0.0007389609,0.0007908166,0.0004206983,0.000807808,0.8627458,0.0001287747],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002015306,0.00004613639,0.00003922032,0.00009926561,0.00001603129,0.00002414889,0.9988402,0.00006704422,0.0006665381],"genre_scores_gemma":[0.001550524,0.0001028146,0.0003689626,0.00008441753,0.000009864869,0.0003354099,0.9949152,0.00006427074,0.002568478],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06355947,"threshold_uncertainty_score":0.1950896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321499422128198,"score_gpt":0.3056178436672976,"score_spread":0.2924028494460156,"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."}}