{"id":"W4407127791","doi":"10.2139/ssrn.5055024","title":"Big Data and Machine Learning in ESG Research","year":2025,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Big data; Computer science; Artificial intelligence; Data science; Data mining","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":[0.007763008,0.0004693274,0.0009504347,0.004468706,0.001257254,0.008458311,0.0009163032,0.002961042,0.008104655],"category_scores_gemma":[0.01799863,0.0002966936,0.0003832313,0.01065664,0.0060019,0.01403056,0.002083473,0.003324271,0.0008128379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00378984,"about_ca_system_score_gemma":0.003276058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005641855,"about_ca_topic_score_gemma":0.007542714,"domain_scores_codex":[0.9968449,0.002048747,0.0001412598,0.0003056766,0.0004868133,0.0001725107],"domain_scores_gemma":[0.97143,0.02427979,0.0009932406,0.001286658,0.001176562,0.0008337457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006506182,0.0000660666,0.01080374,0.0004280193,0.000054424,0.00012508,0.0007423603,0.003234713,0.0000893029,0.8377385,0.03441159,0.1122412],"study_design_scores_gemma":[0.000009385987,0.00001734139,0.00366512,0.0005690968,0.00001232275,0.00006866585,0.001182786,0.007094841,0.0001038372,0.9416432,0.04560841,0.00002503138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0536013,0.2550029,0.0728643,0.4303089,0.008548662,0.000130309,0.002602553,0.0003135013,0.1766275],"genre_scores_gemma":[0.8038059,0.1044095,0.03434343,0.02363043,0.01449882,0.0002085422,0.0009036837,0.0001597452,0.01803999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008458311,"threshold_uncertainty_score":0.0410552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1487402030977672,"score_gpt":0.359052732344852,"score_spread":0.2103125292470848,"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."}}