{"id":"W3135881388","doi":"10.1111/poms.13398","title":"Can It Clean Up Your Inbox? Evidence from South Korean Anti‐spam Legislation","year":2021,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Legislation; Cybercrime; Business; The Internet; Productivity; Opt-in email; Spamming; Internet privacy; Economics; Political science; Law; Computer science; Economic growth; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002700489,0.0001119953,0.00009476927,0.0001151773,0.000435721,0.000584886,0.000170635,0.00003303141,0.00003719409],"category_scores_gemma":[0.0001098168,0.0001137433,0.00002910136,0.0004669917,0.00002512383,0.000906631,0.0001627726,0.00009811842,0.00003001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004881223,"about_ca_system_score_gemma":0.00003257526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002650539,"about_ca_topic_score_gemma":0.0006114435,"domain_scores_codex":[0.9987684,0.00008891681,0.0001984534,0.0005781363,0.0002317883,0.0001343292],"domain_scores_gemma":[0.9992306,0.00001148445,0.0000451404,0.000511424,0.0001454773,0.0000558547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004581135,0.0005552171,0.01947356,0.0002071746,0.0005085284,0.00007146889,0.0717142,0.0611122,0.02047521,0.09586047,0.04532507,0.6846511],"study_design_scores_gemma":[0.002055487,0.000375782,0.2227843,0.001054028,0.0004542949,0.0001219633,0.01636843,0.5096317,0.1515849,0.009733192,0.08334412,0.002491834],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2752846,0.0005440008,0.6174182,0.09822073,0.005534124,0.0007132104,0.000008307179,0.000427455,0.001849362],"genre_scores_gemma":[0.9815169,0.0003672981,0.01167083,0.0005324167,0.0002947286,0.0000297119,0.00002408027,0.000007556117,0.005556472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7062323,"threshold_uncertainty_score":0.5640069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04535849325786089,"score_gpt":0.2654220848146064,"score_spread":0.2200635915567455,"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."}}