{"id":"W4416390170","doi":"10.54254/2755-2721/2025.29791","title":"The Industrial-Level Effects of Climate Change: Evidence from the Health Industry, Wheat Industry, Potatoes Industry, and Corns Industry","year":2025,"lang":"","type":"article","venue":"Applied and Computational Engineering","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Climate change; Productivity; Agriculture; Extreme weather; Crop productivity; Adverse weather; Food industry; Agricultural productivity; Production (economics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0007750944,0.0006458246,0.000687144,0.00006075709,0.001065379,0.0005210972,0.0006110472,0.0027942,0.00003671614],"category_scores_gemma":[0.0004175354,0.000283554,0.0000966609,0.001237123,0.0003762311,0.0002418896,0.000720443,0.005138523,0.000002604382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000128353,"about_ca_system_score_gemma":0.0001402931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001376121,"about_ca_topic_score_gemma":0.0001921781,"domain_scores_codex":[0.9967734,0.0001811515,0.0008330592,0.0007429062,0.0005785592,0.0008909099],"domain_scores_gemma":[0.9938333,0.004926383,0.0004827139,0.0001987457,0.0001493542,0.0004094763],"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":[0.0005581681,0.0005273611,0.1374016,0.001173129,0.001057479,0.00002674472,0.005427966,0.01019556,0.009948642,0.01832373,0.01141398,0.8039456],"study_design_scores_gemma":[0.001236586,0.0003743084,0.9800054,0.004480074,0.000173331,0.00002340326,0.004243348,0.004758243,0.0005689139,0.0008059852,0.002623219,0.0007072286],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9549275,0.008799644,0.00002974504,0.03342862,0.0007094019,0.001510671,0.0004499468,0.00006969105,0.00007476482],"genre_scores_gemma":[0.9931707,0.003562836,0.00007635251,0.001839224,0.00102867,0.0001504045,0.00008155878,0.00001029225,0.0000800073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8426037,"threshold_uncertainty_score":0.9999617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05747259271683687,"score_gpt":0.270994951945712,"score_spread":0.2135223592288751,"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."}}