{"id":"W2943586736","doi":"10.24215/26183188e018","title":"Políticas públicas de vivienda: impactos y limitaciones del Programa ProCreAr","year":2019,"lang":"es","type":"article","venue":"Ciencia, tecnología y política/Ciencia, tecnología y política","topic":"Latin American Urban Studies","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Political science; Humanities; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029983,0.0004423015,0.0005434557,0.001545793,0.001046388,0.003938655,0.0007919948,0.001059596,0.0157534],"category_scores_gemma":[0.009915092,0.0002206263,0.000472555,0.002959649,0.001568812,0.001696522,0.002084601,0.001061364,0.0006454505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008294265,"about_ca_system_score_gemma":0.006771194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0523555,"about_ca_topic_score_gemma":0.05901147,"domain_scores_codex":[0.9967763,0.001287954,0.00007166415,0.0003959849,0.0008333068,0.0006348076],"domain_scores_gemma":[0.9918903,0.003623745,0.002040133,0.0004085938,0.001267372,0.0007697987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002522351,0.001586223,0.3295308,0.0024798,0.0005229469,0.0008720363,0.01823101,0.04316555,0.006527497,0.2409726,0.01967617,0.333913],"study_design_scores_gemma":[0.000249663,0.001417271,0.6924942,0.001238481,0.0004863349,0.0002825819,0.02570077,0.01943115,0.002845868,0.03650248,0.2192722,0.00007902265],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8384937,0.003595289,0.005409949,0.008144121,0.00006232831,0.0002924473,0.001298736,0.0002124897,0.1424909],"genre_scores_gemma":[0.9808755,0.001805695,0.001393209,0.0002521333,0.00004516751,0.0002498421,0.0003421601,0.00003445275,0.01500196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0523555,"threshold_uncertainty_score":0.1041015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635328578560611,"score_gpt":0.3231373765087249,"score_spread":0.3067840907231187,"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."}}