{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01882064,0.0004426698,0.0005329677,0.001579922,0.001674466,0.002275968,0.001345078,0.001635958,0.01371532],"category_scores_gemma":[0.05929948,0.0004695842,0.0007343563,0.00185627,0.003344501,0.003098711,0.001868495,0.002319924,0.001702387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001548143,"about_ca_system_score_gemma":0.002680693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01050722,"about_ca_topic_score_gemma":0.0114191,"domain_scores_codex":[0.9830583,0.01116836,0.00136145,0.001676107,0.001706352,0.00102943],"domain_scores_gemma":[0.8507872,0.07548834,0.05184808,0.009097474,0.0103791,0.002399817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004951824,0.006686359,0.7989969,0.006936735,0.002007084,0.001304766,0.02826912,0.0007354019,0.001181282,0.02046635,0.01810609,0.1103582],"study_design_scores_gemma":[0.0005587317,0.001977833,0.9113942,0.003679955,0.001805289,0.0003944112,0.03576821,0.00116799,0.002181265,0.003547403,0.03741116,0.0001135991],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717086,0.002965189,0.0006828987,0.005587193,0.0001091807,0.0002652742,0.001045024,0.00001304893,0.01762347],"genre_scores_gemma":[0.9944192,0.001561803,0.0002967117,0.002105035,0.00004937419,0.0001146135,0.0003735294,0.00001074017,0.001068946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01882064,"threshold_uncertainty_score":0.09953427,"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."}}