{"id":"W2082663547","doi":"10.5430/air.v1n2p117","title":"Adaboost and SVM based cybercrime detection and prevention model","year":2012,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Computer science; AdaBoost; Cybercrime; Machine learning; Executable; Artificial intelligence; Classifier (UML); Data mining; Software; Pattern recognition (psychology); The Internet; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002279846,0.00008920734,0.00008436236,0.0002487452,0.0003989461,0.0002793374,0.0002124698,0.00008865485,0.00001362241],"category_scores_gemma":[0.0002315518,0.00008715445,0.00002493856,0.0005120146,0.0001323688,0.0008734806,0.0001574456,0.000290059,0.00006547768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005193831,"about_ca_system_score_gemma":0.00005201454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003448103,"about_ca_topic_score_gemma":0.0002328669,"domain_scores_codex":[0.9984534,0.0002218932,0.0001820565,0.0003051421,0.0004047561,0.0004328027],"domain_scores_gemma":[0.9991444,0.0002250716,0.00002730497,0.0002688294,0.0001532637,0.0001811696],"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":[0.00003856213,0.00008932934,0.0002720651,0.00002028125,0.000005783009,0.000001025019,0.001073207,0.0003127511,0.05515805,0.04553632,0.00004157985,0.897451],"study_design_scores_gemma":[0.00002034097,0.0001636943,0.0007443492,0.00001889969,0.000003242397,0.000008320236,0.0001310367,0.6381605,0.2757279,0.08466962,0.0002291738,0.0001229817],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2135477,0.000256355,0.784795,0.0003126688,0.0001718486,0.0001798374,5.304876e-7,0.00006780015,0.0006682313],"genre_scores_gemma":[0.9932857,0.00004757226,0.006353771,0.00003085185,0.0001338704,0.00002697395,5.892308e-7,0.000007909161,0.0001127891],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8973281,"threshold_uncertainty_score":0.3554055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2550317435761351,"score_gpt":0.417311105255372,"score_spread":0.1622793616792368,"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."}}