{"id":"W4389425556","doi":"10.1093/icesjms/fsad192","title":"Model-informed classification of broadband acoustic backscatter from zooplankton in an <i>in situ</i> mesocosm","year":2023,"lang":"en","type":"article","venue":"ICES Journal of Marine Science","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Environment Research Council; Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada; Ocean Frontier Institute; ArcticNet; Norges Forskningsråd; ConocoPhillips; Sight Research UK; Marine Alliance for Science and Technology for Scotland","keywords":"Zooplankton; Mesocosm; Echo sounding; Arctic; Backscatter (email); Marine Strategy Framework Directive; Broadband; Oceanography; Environmental science; Target strength; Classifier (UML); Remote sensing; Computer science; Geology; Fishery; Artificial intelligence; Ecology; Telecommunications; Ecosystem; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.001855198,0.00009807868,0.0002108063,0.0008661295,0.00006323596,0.0001173712,0.0008582842,0.00004671685,0.0002192374],"category_scores_gemma":[0.0001453422,0.00007643399,0.0000317363,0.001406115,0.0003076242,0.001318039,0.00007896569,0.0002755455,0.00003697828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003779487,"about_ca_system_score_gemma":0.0005195587,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009938094,"about_ca_topic_score_gemma":0.02835371,"domain_scores_codex":[0.9978313,0.00006089015,0.000531943,0.0002088737,0.0009809138,0.0003860932],"domain_scores_gemma":[0.9989156,0.0002899652,0.0002436011,0.0001943843,0.0001848074,0.0001717156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008435778,0.00002797029,0.586576,0.00002117558,0.000002743522,0.00002872276,0.0007334242,0.3349115,0.06510901,0.000001277131,0.00005249137,0.01245134],"study_design_scores_gemma":[0.0002754087,0.00008801204,0.5174717,0.00002855541,0.000003417386,0.000007688189,0.0002048144,0.4796931,0.001108759,0.001053203,0.000008560272,0.00005674648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957787,0.00001810131,0.001112835,0.0002089312,0.0001299326,0.00009530017,0.00001817346,0.000006689029,0.002631307],"genre_scores_gemma":[0.9974412,0.0000962858,0.002294866,0.00004303119,0.00004324492,4.079376e-7,0.000021286,0.0000027048,0.00005701901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1447816,"threshold_uncertainty_score":0.9893763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04930085672034533,"score_gpt":0.3063306784013205,"score_spread":0.2570298216809752,"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."}}