{"id":"W3178013428","doi":"10.18280/ria.350309","title":"A Framework for Anomaly Classification Using Deep Transfer Learning Approach","year":2021,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transfer of learning; Computer science; Artificial intelligence; Preprocessor; Machine learning; Field (mathematics); Anomaly detection; Computer vision; Computer security","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":[0.0002507904,0.0001283567,0.0001545839,0.00007667027,0.0003982205,0.0001731512,0.0004272285,0.000126465,0.00003546602],"category_scores_gemma":[0.00008755037,0.0001422288,0.0001456917,0.0008074081,0.00004458643,0.0002178468,0.00006131349,0.0002225875,0.00003464539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005354884,"about_ca_system_score_gemma":0.0000596508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005983833,"about_ca_topic_score_gemma":0.000001234024,"domain_scores_codex":[0.9986809,0.0000529848,0.0003412843,0.0005501268,0.0001104848,0.0002641955],"domain_scores_gemma":[0.9989294,0.0001435971,0.0000661837,0.0005723667,0.0002140904,0.00007436304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004392214,0.0001603005,0.00008626358,0.00004731166,0.00001252836,0.000001732781,0.0008924739,0.04904547,0.03114433,0.8370701,0.00001784936,0.08151726],"study_design_scores_gemma":[0.00001445312,0.00003565913,0.00002249451,0.00002066933,0.000008589354,0.00003135902,0.0004641036,0.8404408,0.135897,0.0176395,0.005272519,0.0001528964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006620546,0.0001746645,0.9908552,0.0004276944,0.00009297191,0.0003048998,0.000001462853,0.0002648711,0.001257725],"genre_scores_gemma":[0.5771143,0.00003175102,0.4222165,0.00007243539,0.00005996667,0.0001123271,0.000005755537,0.00001161293,0.0003753716],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8194306,"threshold_uncertainty_score":0.5799924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09282876624586345,"score_gpt":0.3164997598376683,"score_spread":0.2236709935918049,"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."}}