{"id":"W4404733215","doi":"10.1016/j.cities.2024.105550","title":"Methodology for Prioritizing Sustainable Urban Regeneration Interventions in Informal Settlements: Case Study in Lima","year":2024,"lang":"en","type":"article","venue":"Cities","topic":"Urban and Rural Development Challenges","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Universidad de Lima; Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica","keywords":"Informal settlements; Urban regeneration; Human settlement; Psychological intervention; Environmental planning; Regeneration (biology); Business; Sustainable development; Geography; Economic growth; Political science; Economics; Medicine; Archaeology","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":[0.01126064,0.0006138465,0.0006162963,0.002921189,0.003901596,0.002343261,0.00221503,0.00173442,0.003560651],"category_scores_gemma":[0.009231045,0.0003869101,0.0007337686,0.003169772,0.001944235,0.001502085,0.003428146,0.0009477649,0.0002936865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005102938,"about_ca_system_score_gemma":0.006841536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025948,"about_ca_topic_score_gemma":0.0251721,"domain_scores_codex":[0.9912093,0.00701287,0.0003210292,0.0003730783,0.0005138156,0.000569949],"domain_scores_gemma":[0.9931558,0.005059713,0.0005309177,0.0002640727,0.000592146,0.0003973664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001032974,0.01314258,0.1293399,0.007041051,0.0002936887,0.02616507,0.2319594,0.03767551,0.008540186,0.1332352,0.008613175,0.4029613],"study_design_scores_gemma":[0.0007202296,0.004076386,0.06488875,0.003038868,0.000378674,0.004819755,0.7123902,0.07331637,0.01250515,0.04215658,0.08140314,0.0003059416],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.861578,0.001063239,0.08831529,0.002476198,0.0000582587,0.01400752,0.0006220728,0.00007772328,0.03180164],"genre_scores_gemma":[0.8490179,0.001056565,0.1389347,0.0002726873,0.00001838302,0.00725634,0.0001959172,0.0000195731,0.003227918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01126064,"threshold_uncertainty_score":0.05955267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1975366953151012,"score_gpt":0.4214437713473864,"score_spread":0.2239070760322852,"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."}}