{"id":"W4385450008","doi":"10.2139/ssrn.4526111","title":"Temperature and Local Industry Concentration","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Business; Industrial organization; Environmental science","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":[0.0003254514,0.0001675321,0.0002255271,0.0007143819,0.0003005857,0.001028822,0.0002665302,0.0004135201,0.01596848],"category_scores_gemma":[0.001667812,0.000196669,0.0005259144,0.00120413,0.0002969996,0.0005498844,0.0004544699,0.0004497384,0.002582408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005522068,"about_ca_system_score_gemma":0.0003427321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02132977,"about_ca_topic_score_gemma":0.03025214,"domain_scores_codex":[0.9997464,0.00008472308,0.00001202228,0.00005225201,0.00002628599,0.0000782127],"domain_scores_gemma":[0.9971411,0.001075041,0.0006114462,0.000174966,0.0003159275,0.0006814345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004937376,0.0001120501,0.992999,0.00001467783,0.0001914229,0.000113311,0.0002192793,0.00103564,0.0007322452,0.0003756466,0.0006212647,0.003091862],"study_design_scores_gemma":[0.000003451927,0.000073909,0.997364,0.000008575118,0.00006441024,0.00006351781,0.0005691078,0.0008000138,0.000307178,0.00009640717,0.000642413,0.000007029236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933089,0.0002872406,0.0001212098,0.0001569421,0.00001583643,0.000003554893,0.0007074018,0.00001552411,0.005383321],"genre_scores_gemma":[0.995971,0.00007733546,0.0000250998,0.00001596699,0.00001388692,0.000002533668,0.0003156086,0.000008518961,0.003569921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02132977,"threshold_uncertainty_score":0.05341989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004675429219689308,"score_gpt":0.2070371558286926,"score_spread":0.2023617266090033,"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."}}