{"id":"W6926354152","doi":"10.25318/9810062101-fra","title":"Groupes de population selon la taille convenable du logement et l'état du logement : Canada, provinces et territoires, régions métropolitaines de recensement et agglomérations de recensement","year":2023,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Context (archaeology); Identification (biology)","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":[0.0008870309,0.00161581,0.001264035,0.003994376,0.001279382,0.002358813,0.002569003,0.001348361,0.01874254],"category_scores_gemma":[0.005965936,0.0005076917,0.001144644,0.009169692,0.0005542218,0.0008253858,0.001247188,0.001925024,0.01617067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007147651,"about_ca_system_score_gemma":0.01609206,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8778375,"about_ca_topic_score_gemma":0.9232299,"domain_scores_codex":[0.998922,0.00007245194,0.0000747809,0.0002864054,0.0003454294,0.0002989223],"domain_scores_gemma":[0.9972331,0.0003799431,0.0002174518,0.0003083586,0.001541733,0.0003194653],"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":[0.00008618568,0.00002820937,0.01423004,0.0003322547,0.00006972371,0.00003113281,0.00009013424,0.0007308798,0.00009273848,0.0007191729,0.9786314,0.004958128],"study_design_scores_gemma":[0.0003207097,0.00001846566,0.1127567,0.0004612163,0.00008857533,0.0001116295,0.0006595439,0.001701131,0.0004300729,0.001114252,0.882275,0.00006271785],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001000406,0.0001185794,0.00005691526,0.00007819664,0.00001661575,0.000009795264,0.9979534,0.0001106343,0.000655469],"genre_scores_gemma":[0.002435309,0.0001017734,0.000227351,0.00003697971,0.00000702177,0.0000416235,0.995277,0.00002951554,0.00184343],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1221625,"threshold_uncertainty_score":0.2457639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007864870498298121,"score_gpt":0.2393687406642649,"score_spread":0.2315038701659667,"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."}}