{"id":"W2135754053","doi":"10.1093/icesjms/fsn061","title":"Acoustic seabed classification: current practice and future directions","year":2008,"lang":"en","type":"article","venue":"ICES Journal of Marine Science","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":255,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada","keywords":"Seabed; Computer science; Sonar; Marine habitats; Temporal scales; Standardization; Matching (statistics); Environmental science; Range (aeronautics); Marine ecosystem; Remote sensing; Data science; Oceanography; Geology; Habitat; Ecosystem; Ecology; Engineering","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":[],"category_scores_codex":[0.0009234485,0.00007785229,0.0001038993,0.00009542509,0.0004577709,0.00007935152,0.0004170158,0.00002086989,0.001641011],"category_scores_gemma":[0.0003903939,0.00005939381,0.00002903968,0.0008303788,0.0009767149,0.001471643,0.000539939,0.0003027656,0.00002465101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001009419,"about_ca_system_score_gemma":0.0001077871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006343592,"about_ca_topic_score_gemma":0.00001863248,"domain_scores_codex":[0.9984565,0.00005091355,0.0002311428,0.0001850972,0.0008578199,0.0002185501],"domain_scores_gemma":[0.9991585,0.0001053712,0.0002180086,0.0001645091,0.0001331068,0.000220489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006248122,0.0001812848,0.1926287,0.00001035733,0.000007146199,0.00004993401,0.0006330046,0.00002715693,0.002863254,0.0001105766,0.001835798,0.8015903],"study_design_scores_gemma":[0.0001487884,0.0001073998,0.3755344,0.00000236786,0.000009801714,0.0008944102,0.0002553105,0.0006477154,0.0000397935,0.00007400539,0.6222152,0.00007080293],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.544702,0.0003206091,0.0003738762,0.008083109,0.001221529,0.0001837474,0.000001584285,0.00002283819,0.4450907],"genre_scores_gemma":[0.9780313,0.01285929,0.006650778,0.0001864049,0.0007154483,0.000004402635,6.082752e-7,0.000008896368,0.001542875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8015195,"threshold_uncertainty_score":0.9992716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02918775312644861,"score_gpt":0.3073594164166744,"score_spread":0.2781716632902258,"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."}}