{"id":"W144859847","doi":"10.5555/1999416.1999475","title":"On simulating episodic events against a background of noise-like non-episodic events","year":2010,"lang":"en","type":"article","venue":"Summer Computer Simulation Conference","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Noise (video); Event (particle physics); Computer science; Process (computing); Field (mathematics); Seismology; Physics; Geology; Artificial intelligence; Mathematics; Quantum mechanics","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":[0.0002260206,0.0002461797,0.0002749653,0.00009129393,0.0001059911,0.00002274824,0.0003579183,0.0002946799,0.00005031702],"category_scores_gemma":[0.0000846132,0.0002287049,0.0001262071,0.0001307926,0.0001298346,0.000009456645,0.0001845439,0.0002578162,0.0000344697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000100226,"about_ca_system_score_gemma":0.00008852335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001961459,"about_ca_topic_score_gemma":0.00002634995,"domain_scores_codex":[0.9984149,0.00007825821,0.0004212741,0.0004922245,0.0002898455,0.0003034885],"domain_scores_gemma":[0.998764,0.0001678576,0.0002326894,0.000491366,0.0002178547,0.000126187],"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":[0.0005235749,0.001186071,0.1211303,0.0002505562,0.000386741,0.00001357377,0.0006147639,0.1466367,0.1673073,0.0009096106,0.00148081,0.5595599],"study_design_scores_gemma":[0.003638465,0.00115522,0.1121503,0.0002790232,0.00004653008,0.000003784927,0.00007982831,0.8588579,0.009358237,0.001118366,0.01240311,0.0009092333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8738956,0.00002423844,0.1246668,0.00005599554,0.0008293375,0.0001760824,0.00001504645,0.00002855619,0.0003083016],"genre_scores_gemma":[0.9933706,0.000008491635,0.005595414,0.0004489879,0.0002599257,0.000007757342,0.0001374222,0.00002128353,0.0001501219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7122212,"threshold_uncertainty_score":0.9326315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03577969889429551,"score_gpt":0.3098867298111211,"score_spread":0.2741070309168256,"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."}}