{"id":"W4415209017","doi":"10.3390/en18205421","title":"A Data-Driven Decision-Making Tool for Prioritizing Resilience Strategies in Cold-Climate Urban Neighborhoods","year":2025,"lang":"en","type":"article","venue":"Energies","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Resilience (materials science); Probabilistic logic; Prioritization; Component (thermodynamics); Urban resilience; Extreme weather; Energy (signal processing); Psychological resilience","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":[0.00784127,0.001689872,0.001265367,0.005474475,0.0009465291,0.003504464,0.001768866,0.001190873,0.007886938],"category_scores_gemma":[0.02098235,0.0006858383,0.001596883,0.002966016,0.000559175,0.002593895,0.002539797,0.001235238,0.0009944803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001906178,"about_ca_system_score_gemma":0.003198001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007450919,"about_ca_topic_score_gemma":0.01430166,"domain_scores_codex":[0.9971166,0.00119412,0.0004291113,0.0004477005,0.0006613925,0.0001511798],"domain_scores_gemma":[0.9841075,0.01158854,0.001145514,0.001018924,0.001653593,0.0004860837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008731485,0.001048801,0.02112833,0.001629021,0.0006292625,0.0007396028,0.001904825,0.6391959,0.006103327,0.03471991,0.01265849,0.2793695],"study_design_scores_gemma":[0.0001187385,0.0001851839,0.0020235,0.0002450553,0.0000979021,0.00008146434,0.000663812,0.9570274,0.004305235,0.02516296,0.01000821,0.00008055388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.108248,0.0002547665,0.8478208,0.001118014,0.0001079299,0.001585891,0.01493748,0.01288293,0.01304428],"genre_scores_gemma":[0.3317288,0.0001404591,0.6604654,0.0001393301,0.00001992884,0.001477035,0.005024222,0.0001835296,0.0008212387],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007886938,"threshold_uncertainty_score":0.0414691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00853386597997624,"score_gpt":0.2861837507216109,"score_spread":0.2776498847416347,"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."}}