{"id":"W4396754180","doi":"10.1093/cybsec/tyae006","title":"The simple economics of an external shock to a bug bounty platform","year":2024,"lang":"en","type":"article","venue":"Journal of Cybersecurity","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"Tel Aviv University","keywords":"Shock (circulatory); Hacker; Vulnerability (computing); Computer security; Set (abstract data type); Download; Coronavirus disease 2019 (COVID-19); Software; Business; Computer science; Economics; Internet privacy; World Wide Web; Operating system","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":[0.001664282,0.0005132459,0.0006766585,0.0008000146,0.001097267,0.003927181,0.001071459,0.003648503,0.02004197],"category_scores_gemma":[0.01085046,0.0005120077,0.0005593099,0.000608728,0.002332987,0.00293756,0.002154167,0.002921016,0.001107989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00279686,"about_ca_system_score_gemma":0.001029266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006188988,"about_ca_topic_score_gemma":0.003500703,"domain_scores_codex":[0.9992718,0.0002288625,0.00003040862,0.0001200678,0.00008291571,0.0002659345],"domain_scores_gemma":[0.9919044,0.003967785,0.001837015,0.0003948227,0.0004177088,0.001478235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.004272921,0.003195768,0.07809261,0.0007822005,0.000301545,0.006432233,0.001082527,0.2804805,0.01657198,0.5185044,0.03191484,0.05836845],"study_design_scores_gemma":[0.001338372,0.003790169,0.1101587,0.0002913226,0.0002836004,0.001503688,0.004160346,0.4296918,0.004270288,0.4139822,0.02996247,0.0005670725],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9026647,0.0006264505,0.02098703,0.01078112,0.0002624861,0.0002745906,0.001366353,0.0002928348,0.06274445],"genre_scores_gemma":[0.9909856,0.0001783944,0.0006953555,0.0004004235,0.00006366389,0.00004635712,0.00006504225,0.00001630614,0.007548848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02004197,"threshold_uncertainty_score":0.06704706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360280976856157,"score_gpt":0.2275271374255277,"score_spread":0.2139243276569661,"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."}}