{"id":"W2937782710","doi":"10.1111/irfi.12265","title":"Do Patented Innovations Reduce Stock Price Crash Risk?*","year":2019,"lang":"en","type":"article","venue":"International Review of Finance","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Qatar University; National Natural Science Foundation of China","keywords":"Information asymmetry; Business; Corporate governance; Stock price; Crash; Equity (law); Stock (firearms); Sample (material); Large sample; Monetary economics; Actuarial science; Finance; Economics; Computer science","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":[0.0014705,0.0001136645,0.0002733209,0.0007945055,0.0001614842,0.0009857438,0.000279598,0.001078804,0.003714008],"category_scores_gemma":[0.01890719,0.00009294576,0.0004660331,0.0006339608,0.0003835837,0.0007960197,0.000317808,0.0006942635,0.0003838461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002284812,"about_ca_system_score_gemma":0.0003163154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00153329,"about_ca_topic_score_gemma":0.001504949,"domain_scores_codex":[0.999414,0.0001648662,0.0000646645,0.0001096505,0.0001474911,0.00009928494],"domain_scores_gemma":[0.9803076,0.007342374,0.00953207,0.0007306003,0.001144694,0.000942676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005501959,0.0003824575,0.9564175,0.0001137188,0.0003803961,0.0002758155,0.000118439,0.0008912354,0.001449778,0.0008849473,0.0009561177,0.03757932],"study_design_scores_gemma":[0.00004339009,0.0004695363,0.993537,0.00003143145,0.0001931447,0.0002222012,0.00009552017,0.001625987,0.0008040445,0.0017657,0.001203456,0.000008622596],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905102,0.004700039,0.0004847162,0.001260173,0.00004250139,0.00001247994,0.0002949608,0.0000163332,0.002678628],"genre_scores_gemma":[0.9991329,0.0004495596,0.00003859869,0.00005035928,0.00005112935,0.000001670826,0.00004966996,8.060985e-7,0.0002253961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003714008,"threshold_uncertainty_score":0.01242453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221148778261069,"score_gpt":0.2658107359336996,"score_spread":0.2435992481510889,"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."}}