{"id":"W4388917354","doi":"10.23977/jeis.2023.080507","title":"Optimized Application of Multibeam Bathymetry Technology in Seafloor Surveys","year":2023,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bathymetry; Point (geometry); Terrain; Line (geometry); Geodesy; Underwater; Position (finance); Line width; Geology; Trigonometric functions; Geometry; Mathematics; Optics; Physics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005555056,0.0005748725,0.0003498583,0.0007914255,0.000208823,0.0005081742,0.0004222721,0.0003308746,0.0005593075],"category_scores_gemma":[0.00131201,0.0003127893,0.0003160883,0.0009051735,0.0002063322,0.0009972849,0.0007686825,0.0002207821,0.000260653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003407943,"about_ca_system_score_gemma":0.0004937276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001970715,"about_ca_topic_score_gemma":0.004290503,"domain_scores_codex":[0.9991933,0.0002543638,0.00002911036,0.0001436017,0.0002985606,0.00008113743],"domain_scores_gemma":[0.9995247,0.0001567837,0.0001060126,0.00007543699,0.0001185432,0.00001847729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001834691,0.00008488914,0.02458824,0.0003023182,0.00007702195,0.0002016416,0.0003427087,0.3853374,0.2142756,0.005104905,0.0008139125,0.3686878],"study_design_scores_gemma":[0.00001927094,0.0003994097,0.02004526,0.00003123985,0.00003971886,0.0002601764,0.0002120854,0.915693,0.05780608,0.001975519,0.003469814,0.00004849037],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09807441,0.000324411,0.8995014,0.00006609875,0.00001811259,0.00002964458,0.00007370643,0.0002538613,0.001658374],"genre_scores_gemma":[0.7155067,0.000368042,0.2830781,0.00003891882,0.00001202302,0.00005529433,0.0001154766,0.00004311188,0.0007824016],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001970715,"threshold_uncertainty_score":0.003918469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01067822549625366,"score_gpt":0.2657237689546647,"score_spread":0.255045543458411,"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."}}