{"id":"W3217803042","doi":"10.33423/jabe.v22i3.2862","title":"Economic Outcomes of Corporate Espionage","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Business and Economics","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Industrial espionage; Espionage; Punishment (psychology); Event (particle physics); Business; Event study; Trade secret; Economics; Monetary economics; Law; Intellectual property; Political science; Psychology; Social psychology; History","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":[0.001702231,0.0001671246,0.0002811808,0.001194975,0.0004029901,0.001330998,0.0002198777,0.0005783508,0.002619481],"category_scores_gemma":[0.01576394,0.00008702146,0.0002624714,0.000873443,0.0008889874,0.0008202126,0.001068517,0.0009354963,0.0002576669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007142662,"about_ca_system_score_gemma":0.0002521547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001456975,"about_ca_topic_score_gemma":0.001800631,"domain_scores_codex":[0.998442,0.0004724663,0.0001421892,0.0001222031,0.000533159,0.0002879768],"domain_scores_gemma":[0.9726087,0.007424917,0.01666673,0.0007080701,0.001430423,0.001161246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005402357,0.0003481696,0.9702221,0.00004562115,0.0001283691,0.001340669,0.0002922042,0.003480172,0.001404983,0.003133619,0.0006416204,0.01842243],"study_design_scores_gemma":[0.000006594285,0.0002103772,0.9945644,0.00001344585,0.00002319559,0.0003623047,0.0004696333,0.001282963,0.0007966236,0.001635943,0.0006181567,0.00001639715],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961487,0.0002072895,0.0001704425,0.0001820863,0.000007283673,0.000009457838,0.0001495105,0.000003897944,0.003121517],"genre_scores_gemma":[0.9994882,0.00008157575,0.00002838117,0.00001478991,0.000009800547,0.000001802592,0.000112397,7.692842e-7,0.0002622574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002619481,"threshold_uncertainty_score":0.009002388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0428174976554387,"score_gpt":0.2440911204101541,"score_spread":0.2012736227547154,"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."}}