{"id":"W7104572198","doi":"10.60918/16262","title":"Assessing the effect of socio-demographic evolution on housing market differentiation","year":2000,"lang":"","type":"article","venue":"","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sorting; State (computer science); Consumption (sociology); Property market; Housing industry","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":[0.001610389,0.000219872,0.0002018667,0.0009906329,0.0004433116,0.0007444372,0.0002474265,0.0003345359,0.002567475],"category_scores_gemma":[0.006944476,0.0001018606,0.0004134454,0.001190472,0.0007495835,0.0005108536,0.0005721012,0.0004545986,0.0002435417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001007426,"about_ca_system_score_gemma":0.0005734102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04322309,"about_ca_topic_score_gemma":0.06359001,"domain_scores_codex":[0.9990823,0.0004161995,0.00006050638,0.0001238873,0.0001661542,0.0001509523],"domain_scores_gemma":[0.9903125,0.00495496,0.002244985,0.0004288915,0.00100951,0.001049189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009967019,0.00003756625,0.9956381,0.000004430172,0.00004010242,0.00003441594,0.0001224089,0.0002426875,0.0002902866,0.00004668673,0.00002809263,0.003415639],"study_design_scores_gemma":[3.137712e-7,0.00003756671,0.9995517,5.201489e-7,0.000004805599,0.000007866393,0.00009213413,0.0002008435,0.0000563635,0.000006192589,0.00004050337,0.000001144636],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990419,0.00008550979,0.0001487651,0.00003452339,0.000001910355,0.000005562305,0.0001263648,0.000002282528,0.0005532456],"genre_scores_gemma":[0.9996269,0.00002334254,0.00008121081,0.00000674953,0.000003409006,0.000001588725,0.0001380298,6.802126e-7,0.0001179491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04322309,"threshold_uncertainty_score":0.08594298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01370930181281586,"score_gpt":0.2228063390391828,"score_spread":0.2090970372263669,"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."}}