{"id":"W1830540712","doi":"10.1109/oceans.2000.882163","title":"Bottom classification in very shallow water","year":2002,"lang":"en","type":"article","venue":"","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quest University Canada","funders":"Ministère de la Défense Nationale","keywords":"Shore; Echo (communications protocol); Geology; Aliasing; SIGNAL (programming language); Noise (video); Convolution (computer science); Acoustics; Range (aeronautics); Computer science; Sonar; Waves and shallow water; Remote sensing; Ambient noise level; Multivariate statistics; Artificial intelligence; Oceanography; Sound (geography); Filter (signal processing); Computer vision; Engineering; Machine learning","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":[0.0002272641,0.0003293894,0.0003952407,0.002084295,0.0003701713,0.0006528953,0.0002918413,0.0003648159,0.0009131786],"category_scores_gemma":[0.0006345211,0.0001962782,0.0003147601,0.0008505163,0.0002578945,0.000492294,0.0005843444,0.0001699571,0.0006193984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003520662,"about_ca_system_score_gemma":0.0002867018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008405621,"about_ca_topic_score_gemma":0.01144311,"domain_scores_codex":[0.9997659,0.00002427115,0.00002059408,0.0000382462,0.00007695765,0.00007397233],"domain_scores_gemma":[0.9996511,0.00004871928,0.00006202695,0.00002006878,0.0001405701,0.00007744908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001187136,0.00009326811,0.3145359,0.00027181,0.00009067096,0.001062632,0.00050626,0.02634453,0.1817932,0.001547634,0.003133076,0.469434],"study_design_scores_gemma":[0.0000331716,0.0004073851,0.7182446,0.00008984025,0.0001094073,0.0006326555,0.001679715,0.2407457,0.02718918,0.004855333,0.005889121,0.0001239787],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9255089,0.0006208543,0.06897707,0.0000726833,0.00005352996,0.00004443414,0.0005970358,0.0004767021,0.003648815],"genre_scores_gemma":[0.9745539,0.0001954216,0.02214537,0.00003272475,0.00001581972,0.00001496329,0.0009764836,0.0000405042,0.002024835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008405621,"threshold_uncertainty_score":0.01671338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06094367580599205,"score_gpt":0.2447963938233314,"score_spread":0.1838527180173394,"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."}}