{"id":"W77960026","doi":"10.1609/aaai.v27i1.8553","title":"Towards Cohesive Anomaly Mining","year":2013,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Office of International Science and Engineering; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Cluster analysis; Computer science; Task (project management); Data mining; Set (abstract data type); Anomaly detection; Anomaly (physics); Data set; Big data; Artificial intelligence; Engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006332002,0.002019874,0.002829867,0.006546276,0.002039241,0.003457096,0.004551879,0.002593885,0.000828445],"category_scores_gemma":[0.02442102,0.00122063,0.001910374,0.006526904,0.002787631,0.004669923,0.007605898,0.003878481,0.0007055011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006710632,"about_ca_system_score_gemma":0.001565526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001774314,"about_ca_topic_score_gemma":0.002266593,"domain_scores_codex":[0.9927828,0.00223875,0.0003990412,0.0018983,0.002335052,0.0003459968],"domain_scores_gemma":[0.9859537,0.006771447,0.001701829,0.00269911,0.002478686,0.0003952169],"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":[0.0002952817,0.0005586751,0.02717945,0.0007490765,0.0009154445,0.001035489,0.00245912,0.2080688,0.01651984,0.1331036,0.01012978,0.5989856],"study_design_scores_gemma":[0.00002624284,0.00009518846,0.001782929,0.00005700096,0.00008276192,0.0004417475,0.0002808992,0.8066686,0.002975051,0.1810177,0.00653141,0.00004048555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01058654,0.000337733,0.9876965,0.0002440782,0.0000309703,0.00008885897,0.00007800187,0.0004473911,0.0004900064],"genre_scores_gemma":[0.2402335,0.0005666463,0.7556237,0.0004510613,0.0002811289,0.0003494074,0.0009274632,0.000208702,0.001358321],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006546276,"threshold_uncertainty_score":0.0334872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06691446556035674,"score_gpt":0.2859611338256471,"score_spread":0.2190466682652903,"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."}}