{"id":"W4416624434","doi":"10.3390/jrfm18120669","title":"Does Litigation Risk Affect Meeting-or-Beating Earnings Expectations? Evidence from Quasi-Natural Experiment","year":2025,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Ninth; Affect (linguistics); Litigation risk analysis; Causality (physics); Benchmark (surveying)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.02067702,0.0003712115,0.0007978662,0.000282519,0.001134533,0.001784626,0.001071439,0.001749894,0.01061133],"category_scores_gemma":[0.03643195,0.0004884432,0.0008198716,0.000223792,0.001927085,0.001228253,0.0007447799,0.001809829,0.001263789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005593096,"about_ca_system_score_gemma":0.001418862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001090396,"about_ca_topic_score_gemma":0.001030027,"domain_scores_codex":[0.9869308,0.008441806,0.0007076443,0.00172653,0.001413498,0.000779736],"domain_scores_gemma":[0.9124755,0.05398974,0.0216904,0.008300948,0.001358534,0.002184932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.1122959,0.3177511,0.3995217,0.001365435,0.00196557,0.00107914,0.007658795,0.002502461,0.03096664,0.02256984,0.005525898,0.09679741],"study_design_scores_gemma":[0.01626853,0.2486995,0.663515,0.0002747893,0.001335783,0.0004676335,0.00321093,0.01278654,0.01330367,0.02384027,0.01601016,0.0002871379],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918346,0.000124294,0.002230393,0.0003292136,0.0001019461,0.00149392,0.0002965406,0.00002334544,0.003565714],"genre_scores_gemma":[0.9891508,0.0001303378,0.003219191,0.0005364736,0.00007153342,0.003019773,0.0002064502,0.000008895955,0.003656512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02067702,"threshold_uncertainty_score":0.1093518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006489010717825761,"score_gpt":0.2324420337711156,"score_spread":0.2259530230532898,"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."}}