{"id":"W1972503266","doi":"10.1109/tsmcb.2012.2224339","title":"Learning-Automaton-Based Online Discovery and Tracking of Spatiotemporal Event Patterns","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Event (particle physics); Correctness; Machine learning; Adaptation (eye); Scheme (mathematics); Artificial intelligence; Theoretical computer science; Distributed computing; Data mining; Algorithm","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":[0.0001805468,0.0001169125,0.0001343408,0.0001285422,0.00008742279,0.00007138075,0.0001779217,0.00006098637,0.00002327777],"category_scores_gemma":[0.000006107844,0.0001124049,0.00006109059,0.0001854334,0.00004664695,0.0004163925,0.000003068281,0.0002178053,0.000004708248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002670887,"about_ca_system_score_gemma":0.00004745474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000473759,"about_ca_topic_score_gemma":0.0000317796,"domain_scores_codex":[0.9989889,0.00009427426,0.0002457314,0.0001708306,0.0002736071,0.0002266359],"domain_scores_gemma":[0.9993954,0.0001152471,0.00009102256,0.00022034,0.00006426997,0.0001137738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002991039,0.002127228,0.01981206,0.0001644197,0.00006604186,0.000003801774,0.003335858,0.8006685,0.0011104,0.001583789,0.00003729942,0.1710607],"study_design_scores_gemma":[0.0007603053,0.0003996104,0.01824239,0.0001099812,0.0000205449,0.000006795663,0.00008757327,0.9501648,0.02949688,0.00005126408,0.0003924508,0.0002674048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1995929,0.00002505169,0.7997115,0.0002371542,0.0001936677,0.0001123849,0.00002046275,0.00007097433,0.00003592089],"genre_scores_gemma":[0.9859841,0.00005804967,0.01359282,0.00009309613,0.00001988675,0.000006632535,0.000006309131,0.00001298451,0.0002260534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7863913,"threshold_uncertainty_score":0.4583738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0221934737989136,"score_gpt":0.2714264566596944,"score_spread":0.2492329828607809,"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."}}