{"id":"W124750358","doi":"10.2139/ssrn.2148741","title":"Markets Can Cure Spam Zombies","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Spamming; Business; Internet privacy; Advertising; Computer science; World Wide Web; The Internet","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":[0.001460531,0.0005962563,0.0006185999,0.002216203,0.00206745,0.002928511,0.0005753417,0.002707795,0.02744671],"category_scores_gemma":[0.008233119,0.000255229,0.0004311631,0.0009613278,0.001497128,0.004733081,0.001933408,0.001787331,0.005602548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006579226,"about_ca_system_score_gemma":0.001039089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002387552,"about_ca_topic_score_gemma":0.003905257,"domain_scores_codex":[0.9992689,0.0002339895,0.00001802473,0.0000753251,0.000208108,0.0001957007],"domain_scores_gemma":[0.997286,0.0009621058,0.000447136,0.000351017,0.0005486594,0.0004051793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007451914,0.001071001,0.02049739,0.0006173247,0.0002171001,0.0007314823,0.00157921,0.005561733,0.00744513,0.1665058,0.2225311,0.5724975],"study_design_scores_gemma":[0.000522762,0.0009625776,0.02956698,0.0007719098,0.0002893055,0.001487514,0.005398073,0.04364048,0.01053509,0.4589337,0.4477767,0.000115035],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3179826,0.02067372,0.08514586,0.1159832,0.00479344,0.0005454802,0.001241313,0.007596162,0.4460383],"genre_scores_gemma":[0.9278916,0.003199155,0.01050023,0.006640714,0.0009696969,0.00008737249,0.0002559724,0.0002439284,0.05021137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02744671,"threshold_uncertainty_score":0.09181839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004717552186643518,"score_gpt":0.2079410794353455,"score_spread":0.203223527248702,"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."}}