{"id":"W2620578829","doi":"","title":"Plex de Montréal : portrait et singularités des logements caractéristiques montréalais","year":2017,"lang":"fr","type":"article","venue":"INRIA a CCSD electronic archive server","topic":"Social Sciences and Governance","field":"Social Sciences","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","sts"],"consensus_categories":[],"category_scores_codex":[0.001777267,0.000414038,0.0004667632,0.00004834947,0.00331256,0.0006072538,0.001561701,0.0002789485,0.0005665737],"category_scores_gemma":[0.0006664466,0.0004369761,0.0003594478,0.0002147591,0.002340411,0.001286879,0.000379402,0.0007639694,0.0001138743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001232415,"about_ca_system_score_gemma":0.001966228,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5723549,"about_ca_topic_score_gemma":0.885895,"domain_scores_codex":[0.9951132,0.0006526656,0.0004489759,0.0007191969,0.0008281148,0.002237823],"domain_scores_gemma":[0.997913,0.0001714226,0.0006796471,0.0006697889,0.0001361274,0.0004300358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001331091,0.0003632544,0.09455734,0.00006034462,0.0003286473,0.0001590124,0.0410779,0.0001151998,0.0002820464,0.7680842,0.02359156,0.07124737],"study_design_scores_gemma":[0.0005926156,0.0002362713,0.4331298,0.0001519498,0.0001039164,0.00001182041,0.001280738,0.0005701129,0.00005034985,0.236091,0.3272909,0.0004905198],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9022428,0.02198431,0.001557351,0.03070294,0.001059085,0.0005462813,0.0001462137,0.00009963602,0.04166135],"genre_scores_gemma":[0.9727105,0.009426747,0.0008923297,0.0009459504,0.0008071346,0.00003753489,0.00001227099,0.00004307633,0.01512441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5319933,"threshold_uncertainty_score":0.9998082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02728545751256178,"score_gpt":0.3295071329795817,"score_spread":0.3022216754670199,"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."}}