{"id":"W4404688570","doi":"10.1109/oceans55160.2024.10754209","title":"Validating a Chaos Based Anoxic Event Prediction Method for Estuaries","year":2024,"lang":"en","type":"article","venue":"","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Fisheries and Oceans Canada; National Research Council Canada","funders":"National Research Council Canada; Canadian Space Agency; Environment and Climate Change Canada; Canadian Food Inspection Agency","keywords":"Anoxic waters; CHAOS (operating system); Computer science; Event (particle physics); Environmental science; Oceanography; Geology; Physics; Computer security","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":[0.001553644,0.001024635,0.0004860068,0.001271919,0.0005759389,0.0007074579,0.001095997,0.0008925212,0.0008712408],"category_scores_gemma":[0.003645003,0.0002065542,0.0007544053,0.000814549,0.0002770583,0.0007275015,0.0006736542,0.0007640906,0.0004238676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007572515,"about_ca_system_score_gemma":0.001029613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01551788,"about_ca_topic_score_gemma":0.02212125,"domain_scores_codex":[0.9994018,0.0001312159,0.00007480248,0.0002190637,0.0001275035,0.00004558268],"domain_scores_gemma":[0.9979345,0.0007832312,0.000188452,0.0004100307,0.0006095025,0.00007443666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006325642,0.0009845766,0.08131156,0.0002872436,0.0004321503,0.0004323451,0.0001868709,0.6948109,0.02650696,0.001287772,0.01004396,0.1830832],"study_design_scores_gemma":[0.00002879592,0.0001157449,0.01506267,0.00001318618,0.0000221167,0.00004942812,0.00004442043,0.9723732,0.01035652,0.0004306382,0.001480368,0.00002292747],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8461927,0.0002078573,0.1355392,0.0002856216,0.0001528005,0.0002906343,0.01093525,0.004475914,0.001919956],"genre_scores_gemma":[0.8694472,0.0001042883,0.1037182,0.00005806682,0.0000326331,0.0002822521,0.02476825,0.0001492525,0.001439902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01551788,"threshold_uncertainty_score":0.03085512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463218685553371,"score_gpt":0.2602863149710373,"score_spread":0.2456541281155036,"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."}}