{"id":"W4226182561","doi":"10.2139/ssrn.4050189","title":"Say More to Return Less? Disclosure Subsequent to Successful Technological Innovation","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Business; Industrial organization; Accounting","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":[0.002976454,0.00008365967,0.0002305221,0.0004783834,0.001006533,0.002317071,0.0002978934,0.002281909,0.007034528],"category_scores_gemma":[0.044168,0.00013826,0.0002893233,0.000668501,0.001082418,0.001653146,0.001370539,0.002243451,0.0006272942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000714172,"about_ca_system_score_gemma":0.001149355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001486883,"about_ca_topic_score_gemma":0.001778227,"domain_scores_codex":[0.9984843,0.000570476,0.0001022426,0.00009911826,0.0003010635,0.000442802],"domain_scores_gemma":[0.9631609,0.02038844,0.01136549,0.001686361,0.001391122,0.002007654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004382387,0.00285544,0.6457347,0.0003359354,0.0002262779,0.007076441,0.02179963,0.001203312,0.003975415,0.06499829,0.01675781,0.2306544],"study_design_scores_gemma":[0.0002000127,0.001260388,0.8496747,0.0003849188,0.0002212841,0.006978838,0.02990337,0.002334225,0.004187279,0.07894552,0.0257836,0.0001258753],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9564394,0.0009523775,0.0003380387,0.02500164,0.0002123563,0.00001879972,0.0001160924,0.00001664648,0.01690449],"genre_scores_gemma":[0.9964855,0.0003052835,0.00008933628,0.00113157,0.0001452597,0.000005271427,0.00003139048,0.000004668337,0.001801856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007034528,"threshold_uncertainty_score":0.02353287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009583300622297139,"score_gpt":0.2255087852154287,"score_spread":0.2159254845931316,"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."}}