{"id":"W6964152513","doi":"10.25318/3410013301-fra","title":"Société canadienne d'hypothèques et de logement, loyers moyens pour les régions de 10 000 habitants et plus","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Mortgage and Housing Corporation","funders":"","keywords":"Ether cleavage; Problem solver; Context (archaeology)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001704033,0.001443861,0.001251303,0.0006454007,0.0006831978,0.0004956207,0.001227684,0.0007999982,0.006140134],"category_scores_gemma":[0.006808613,0.001866821,0.000141831,0.0006952839,0.0004033415,0.0004175267,0.0002748238,0.00146253,0.0008282646],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.03106741,"about_ca_system_score_gemma":0.02494211,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9256135,"about_ca_topic_score_gemma":0.9985446,"domain_scores_codex":[0.9916075,0.001384413,0.001414211,0.001375932,0.001491211,0.00272667],"domain_scores_gemma":[0.9903533,0.004153946,0.001574163,0.00128522,0.001295574,0.001337737],"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":[0.0001131358,0.0002330141,0.0005905546,0.0009475425,0.0005780961,0.001004719,0.0007302011,0.002230733,0.0006772982,0.01646966,0.9751034,0.001321625],"study_design_scores_gemma":[0.001572442,0.0002717556,0.0510024,0.001562338,0.00198571,0.0001872226,0.005808192,0.007137193,0.0002897138,0.002031069,0.9253087,0.002843248],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003631899,0.0004748022,0.01136621,0.001722165,0.001380268,0.001282341,0.9791565,0.00007566797,0.0009101481],"genre_scores_gemma":[0.01885577,0.0009403274,0.009048559,0.0009257591,0.0002504702,0.0001905883,0.9503235,0.0004658088,0.01899922],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07293113,"threshold_uncertainty_score":0.9999497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0191108775225791,"score_gpt":0.3098279262477807,"score_spread":0.2907170487252015,"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."}}