{"id":"W3126444040","doi":"10.4000/eps.11170","title":"L’identification des micro-zones d’insécurité résidentielle : le cas du marché locatif à Montréal","year":2021,"lang":"fr","type":"article","venue":"Espace populations sociétés","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Art","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007674934,0.0003551894,0.000630165,0.0002791974,0.001206163,0.0006338051,0.0003054897,0.0003936312,0.002667015],"category_scores_gemma":[0.0004640414,0.0005849813,0.0004057735,0.0006719395,0.0003190976,0.0009375105,0.0002270178,0.0003412021,0.001609342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006728754,"about_ca_system_score_gemma":0.0002030491,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01320029,"about_ca_topic_score_gemma":0.02501872,"domain_scores_codex":[0.9970843,0.0001206239,0.001221964,0.000824289,0.00007105171,0.0006777316],"domain_scores_gemma":[0.9980152,0.0001148331,0.0006509637,0.0008416704,0.0002199607,0.0001573717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005363418,0.00144259,0.5499393,0.0005518568,0.0004672679,0.00008788916,0.01294495,0.007688413,0.000299693,0.2580367,0.1174949,0.05099283],"study_design_scores_gemma":[0.001912857,0.00005186868,0.4731809,0.0002253823,0.0001938711,0.0001625946,0.009361606,0.04133507,0.0009828581,0.143793,0.3271231,0.001676869],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7546431,0.08806431,0.03076106,0.091013,0.01249057,0.0005343218,0.0005869853,0.0001560432,0.02175062],"genre_scores_gemma":[0.8824495,0.02162172,0.01085397,0.0002355894,0.0007609281,0.00005589101,0.0004587201,0.0001346645,0.08342899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2096283,"threshold_uncertainty_score":0.9996601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05006663417757762,"score_gpt":0.2830628051932187,"score_spread":0.2329961710156411,"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."}}