{"id":"W3121194732","doi":"10.1111/poms.12803","title":"A Game Between a Terrorist and a Passive Defender","year":2017,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Terrorism, Counterterrorism, and Political Violence","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Terrorism; Stylized fact; Damages; Computer security; Extension (predicate logic); Computer science; Politics; Economics; Political science; Law; Macroeconomics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002257284,0.00008833778,0.00009699353,0.00005848713,0.001699946,0.000483992,0.0001341109,0.00003837461,0.00003426239],"category_scores_gemma":[0.0001035103,0.00008209531,0.00001932095,0.00004011102,0.0003592869,0.0004523738,0.00009364016,0.00007386306,0.00001995949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003687368,"about_ca_system_score_gemma":0.00001790559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000746475,"about_ca_topic_score_gemma":0.001246772,"domain_scores_codex":[0.9991465,0.00005967616,0.0001293196,0.0002995331,0.0001645757,0.0002004564],"domain_scores_gemma":[0.9995111,0.000009336436,0.00003914446,0.0002696442,0.00005596603,0.0001148673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003903504,0.0003229357,0.09903069,0.0002821429,0.0003552025,0.00002893234,0.2792612,0.00002572097,0.0000599446,0.1354537,0.007918212,0.4772223],"study_design_scores_gemma":[0.0009233315,0.0001530244,0.4753444,0.0002755047,0.0003264899,0.000008406184,0.2703983,0.0003114392,0.0001266594,0.006461418,0.2448039,0.0008671507],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9426828,0.0001303515,0.002446613,0.03930373,0.0008650037,0.0007124203,0.0000102133,0.00009182576,0.01375701],"genre_scores_gemma":[0.9920486,0.0005178331,0.0001363454,0.0002077168,0.0005487318,0.00006167519,0.00000357475,0.000005799525,0.00646969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4763551,"threshold_uncertainty_score":0.9995997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03743296032950336,"score_gpt":0.3444482294821078,"score_spread":0.3070152691526044,"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."}}