{"id":"W4310720507","doi":"10.1109/uemcon54665.2022.9965708","title":"Ocean Medical Waste Detection for CPU-Based Underwater Remotely Operated Vehicles (ROVs)","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 13th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Remotely operated underwater vehicle; Underwater; Remotely operated vehicle; Computer science; Marine engineering; Environmental science; Engineering; Artificial intelligence; Automotive engineering; Mobile robot; Geology; Robot; Oceanography","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001814882,0.0006115469,0.0007039086,0.0003550606,0.001788566,0.0003292752,0.00293091,0.000324955,0.0003927204],"category_scores_gemma":[0.00004160661,0.0006944849,0.0002746274,0.0007928362,0.0001981127,0.0002919004,0.0006629096,0.001829171,0.00006709665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009064657,"about_ca_system_score_gemma":0.0006869974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001968864,"about_ca_topic_score_gemma":0.00132602,"domain_scores_codex":[0.9947683,0.001117802,0.001289537,0.0007221659,0.0009567461,0.00114551],"domain_scores_gemma":[0.9957466,0.0005906757,0.0004193665,0.002231224,0.000670285,0.0003418929],"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":[0.0005942202,0.001226245,0.0003116107,0.0005959479,0.0008158594,0.000007365562,0.01199739,0.6903403,0.1080126,0.001911053,0.01401581,0.1701716],"study_design_scores_gemma":[0.001869717,0.0005063323,0.00002223884,0.00009602812,0.00006483566,0.00007438651,0.00203346,0.5619141,0.02083674,0.0005641439,0.4110471,0.0009709198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7282739,0.003196254,0.2632519,0.0007919261,0.000553999,0.001943713,0.0001754896,0.001382856,0.0004299155],"genre_scores_gemma":[0.9944551,0.0006067601,0.001855213,0.0005901266,0.0001767862,0.0003583161,0.001130534,0.0001789048,0.0006482711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3970313,"threshold_uncertainty_score":0.9995506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01885229457353729,"score_gpt":0.2553268089691237,"score_spread":0.2364745143955864,"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."}}