{"id":"W2038425038","doi":"10.1115/omae2011-49024","title":"High Resolution Seabed Sub-Bottom Profiler for AUV","year":2011,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Subsea; Marine engineering; Seabed; Underwater; Bathymetry; Intervention AUV; Engineering; Remotely operated underwater vehicle; Remote sensing; Computer science; Geology; Oceanography; Robot; Mobile robot","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002815776,0.0003317132,0.0002662714,0.0002977969,0.0003234257,0.0004450232,0.0005500797,0.0003979901,0.001717914],"category_scores_gemma":[0.0002806136,0.0002010632,0.0002166973,0.0001421238,0.0001597629,0.0004074377,0.0006242055,0.0004914576,0.00102761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006988115,"about_ca_system_score_gemma":0.0009972616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009451791,"about_ca_topic_score_gemma":0.01683352,"domain_scores_codex":[0.9995665,0.00002571764,0.000009844256,0.00005608819,0.0002905235,0.00005133406],"domain_scores_gemma":[0.9997521,0.00002090113,0.00002035057,0.0000349429,0.000134054,0.00003757911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002062213,0.00006873334,0.004907389,0.0001112123,0.00002043126,0.0002705344,0.0002502724,0.006172244,0.8127195,0.00156351,0.005820662,0.1678894],"study_design_scores_gemma":[0.0001078938,0.002505176,0.04712173,0.00006304141,0.0001004688,0.00167143,0.0004058466,0.1445058,0.693754,0.0006806058,0.1089313,0.0001526938],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3762617,0.0007057886,0.5883095,0.0006425012,0.0002217543,0.0004043919,0.001245464,0.005592858,0.02661604],"genre_scores_gemma":[0.6765244,0.0003219935,0.3010514,0.0002368751,0.00003329415,0.0001917344,0.00106865,0.0001627812,0.02040889],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009451791,"threshold_uncertainty_score":0.01879352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04245322616813196,"score_gpt":0.2108817572956427,"score_spread":0.1684285311275107,"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."}}