{"id":"W2134025716","doi":"10.1002/nav.21513","title":"Accuracy assessment of detection performance for sidescan sonars","year":2012,"lang":"en","type":"article","venue":"Naval Research Logistics (NRL)","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Defence Research and Development Canada","keywords":"Piecewise; Sonar; Computer science; Range (aeronautics); Interval (graph theory); Representation (politics); Function (biology); Logistic regression; Data mining; Marine engineering; Artificial intelligence; Machine learning; Mathematics; Engineering; Aerospace 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01353987,0.0005423783,0.0005476095,0.001368287,0.0002268458,0.0009719728,0.0009777984,0.000760944,0.0007717105],"category_scores_gemma":[0.06786457,0.0002983354,0.0006080362,0.0009205802,0.0006524707,0.0007007241,0.00104361,0.0007210504,0.0002684813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007732773,"about_ca_system_score_gemma":0.0005832165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007248352,"about_ca_topic_score_gemma":0.002472867,"domain_scores_codex":[0.9938608,0.002918565,0.0003632899,0.0006959147,0.001862006,0.0002994224],"domain_scores_gemma":[0.9173855,0.06481452,0.004531929,0.004135426,0.008758103,0.0003746116],"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":[0.003087298,0.0001072901,0.1150362,0.0002532053,0.0004430339,0.0001375005,0.0003608234,0.7417524,0.01198144,0.003065098,0.001086235,0.1226895],"study_design_scores_gemma":[0.00003907104,0.0005986947,0.02795808,0.00004852025,0.00005844398,0.0001238253,0.00009192547,0.9535631,0.01594837,0.00103889,0.0004560758,0.00007504041],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8778472,0.0006043452,0.1181937,0.0001899851,0.0000505292,0.00004811168,0.0003970247,0.0004667791,0.002202247],"genre_scores_gemma":[0.9861135,0.00006814744,0.01328716,0.00001655443,0.000006904823,0.00002000322,0.0002473996,0.00002965874,0.0002106623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01353987,"threshold_uncertainty_score":0.07160652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.556571151684996,"score_gpt":0.6155996670772744,"score_spread":0.05902851539227838,"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."}}