{"id":"W2110809952","doi":"10.22215/etd/2005-08459","title":"A spam-detecting artificial immune system","year":2005,"lang":"en","type":"dissertation","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage; Library and Archives Canada; Carleton University; ASTER","funders":"","keywords":"Computer science; Artificial intelligence","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":[0.0003368113,0.0002315922,0.0002598259,0.0002266826,0.0002533318,0.0004336472,0.000675761,0.000297112,0.00003631808],"category_scores_gemma":[0.00003910736,0.0002254367,0.0001542755,0.0003816856,0.000005181809,0.0003332406,0.00004282969,0.0003613121,0.0004179693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001416738,"about_ca_system_score_gemma":0.00008494372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003852107,"about_ca_topic_score_gemma":0.0008271108,"domain_scores_codex":[0.9984448,0.00005170156,0.0004090614,0.0004843241,0.0003436129,0.0002664914],"domain_scores_gemma":[0.9989838,0.00005086387,0.0002539619,0.0005470411,0.0001043427,0.00005997345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008089469,0.00008787242,0.00001682012,0.0005897274,0.0001240652,0.00004533145,0.005062007,0.0001699185,0.03110614,0.208491,0.0005112864,0.7537149],"study_design_scores_gemma":[0.0006591231,0.0004378321,0.003437286,0.001530725,0.0001597301,0.0002229657,0.008462054,0.2361312,0.7316653,0.002316283,0.01204062,0.002936924],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2316273,0.002344616,0.2510583,0.0004608306,0.04130169,0.001342604,0.000005134867,0.007335758,0.4645237],"genre_scores_gemma":[0.9820844,0.000005088674,0.005643491,0.00002174726,0.001117978,0.00003218051,0.00003402207,0.00002996442,0.01103111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.750778,"threshold_uncertainty_score":0.9193042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321165041939827,"score_gpt":0.2395473651941302,"score_spread":0.2263357147747319,"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."}}