{"id":"W7084601509","doi":"10.17605/osf.io/zn8qe","title":"HeatIN","year":2025,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Economic and Technological Innovation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Socioeconomic status; Extreme heat; Extreme weather; Adaptation (eye); Heat wave; Work (physics)","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":[0.0035084,0.0005487713,0.0006030989,0.001201676,0.001522536,0.003662833,0.001257977,0.001381044,0.3145074],"category_scores_gemma":[0.007816899,0.000294571,0.0005390468,0.001602949,0.000791099,0.002692754,0.003175672,0.001386684,0.1041492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00223309,"about_ca_system_score_gemma":0.006047132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01566775,"about_ca_topic_score_gemma":0.01841056,"domain_scores_codex":[0.9982423,0.0004206417,0.00004771596,0.0002786231,0.0007139127,0.0002968242],"domain_scores_gemma":[0.9933473,0.0008788042,0.000349615,0.001548732,0.001970416,0.001905024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003369468,0.0001027334,0.003752041,0.0002008687,0.00002073493,0.0001042079,0.0002718175,0.0004620331,0.0006281858,0.05932822,0.764764,0.1700281],"study_design_scores_gemma":[0.00003932764,0.00005364701,0.004243367,0.00008632353,0.000006546291,0.00007603168,0.0001340843,0.0006801177,0.0004837465,0.008087898,0.9860913,0.00001753343],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02109427,0.0043514,0.03253463,0.04411352,0.007717769,0.000623016,0.0612673,0.01653705,0.811761],"genre_scores_gemma":[0.1169778,0.003228538,0.02558838,0.004460869,0.001761712,0.0006920257,0.05066678,0.00567302,0.790951],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3145074,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02660093875349131,"score_gpt":0.2380283921008229,"score_spread":0.2114274533473316,"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."}}