{"id":"W4404959867","doi":"10.2139/ssrn.5026580","title":"Hedging Environmental Regulatory Risk through Corporate Innovation","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Corporate Social Responsibility Reporting","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Politics; Sentiment analysis; Business; Political science; Political economy; Economics; Computer science; Natural language processing; Law","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":[0.002262441,0.0003434255,0.0004169625,0.0008548366,0.0003929776,0.003224197,0.0005706224,0.001817828,0.005238521],"category_scores_gemma":[0.01296768,0.0001885465,0.0004705998,0.0005613295,0.001146058,0.003265749,0.001677945,0.001489011,0.0003260905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001459167,"about_ca_system_score_gemma":0.0009543648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001841563,"about_ca_topic_score_gemma":0.002202371,"domain_scores_codex":[0.999109,0.0002540572,0.00003842335,0.000149879,0.0002845808,0.0001640958],"domain_scores_gemma":[0.9890765,0.006578149,0.002131635,0.0009748632,0.0008118113,0.0004270954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0007482664,0.001009162,0.1222314,0.0002039364,0.0004550171,0.001077683,0.001593451,0.1898448,0.008134026,0.4337498,0.004132172,0.2368204],"study_design_scores_gemma":[0.00009044429,0.0006793448,0.06025192,0.00009448274,0.0002681051,0.0002476958,0.001306073,0.2247024,0.004089687,0.6999467,0.008205961,0.0001171861],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8661923,0.0007439297,0.03464562,0.002626053,0.0001214586,0.00004405661,0.00006728486,0.0001623187,0.09539698],"genre_scores_gemma":[0.9960282,0.0001294145,0.0005693389,0.00005060754,0.00002320686,0.00000253262,0.000007842896,0.00000476853,0.003184098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005238521,"threshold_uncertainty_score":0.01752466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01917534489081841,"score_gpt":0.2367724391466692,"score_spread":0.2175970942558507,"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."}}