{"id":"W4387687635","doi":"10.3390/drones7100635","title":"Bubble Plume Tracking Using a Backseat Driver on an Autonomous Underwater Vehicle","year":2023,"lang":"en","type":"article","venue":"Drones","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Underwater; Computer science; Environmental science; Marine engineering; Tracking (education); Grid; Real-time computing; Plume; Bathymetry; Intervention AUV; Remote sensing; Remotely operated underwater vehicle; Geology; Artificial intelligence; Meteorology; Mobile robot; Robot; Engineering; Oceanography; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001056001,0.00007813073,0.00006158755,0.00004105132,0.000177106,0.00004527536,0.00007217186,0.00004498409,0.001217493],"category_scores_gemma":[0.000004982535,0.00007329365,0.00002891272,0.0001943042,0.0000550901,0.0002911254,0.00004135447,0.00005955051,0.003154275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001381336,"about_ca_system_score_gemma":0.000004333671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003280788,"about_ca_topic_score_gemma":0.0001884002,"domain_scores_codex":[0.9993162,0.00003029836,0.00008851489,0.0002139693,0.0001542472,0.0001967337],"domain_scores_gemma":[0.9997634,0.00001093888,0.00002484652,0.0001301823,0.000003354583,0.00006729873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003012009,0.0001388003,0.042105,0.00001272638,0.00001397207,0.00003738881,0.002959335,0.06150055,0.8033078,0.0001878649,0.001009223,0.0886972],"study_design_scores_gemma":[0.00088701,0.0003216042,0.5086398,0.00003614892,0.00002488361,0.00001781944,0.0009309535,0.2463346,0.214895,0.002531248,0.0247796,0.0006013255],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961725,0.000001772273,0.0001904993,0.0001657739,0.0001688441,0.00007662372,0.000001838813,0.0001803789,0.00304178],"genre_scores_gemma":[0.9972603,0.000002914091,0.0001915858,0.0002025992,0.00004653769,0.000005010562,0.000007776453,0.00001521833,0.00226804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5884128,"threshold_uncertainty_score":0.9996955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0294487372065574,"score_gpt":0.2628962800918894,"score_spread":0.233447542885332,"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."}}