{"id":"W2006344374","doi":"10.1109/oceans.2014.7003239","title":"Initial performance analysis on underside iceberg profiling with autonomous underwater vehicle","year":2014,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Iceberg; Underwater; Sonar; Marine engineering; Profiling (computer programming); Underwater glider; Submarine pipeline; Real-time computing; Computer science; Engineering; Geology; Glider; Artificial intelligence; Sea ice; Oceanography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001526576,0.0001552164,0.0002031819,0.000162943,0.000108122,0.0000802529,0.0002128634,0.00005795731,0.00006690963],"category_scores_gemma":[5.085182e-7,0.0001163763,0.00006062455,0.0003404308,0.00002861327,0.0001426121,0.00002910468,0.0001418502,0.0001551957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007063083,"about_ca_system_score_gemma":0.00001026355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004792255,"about_ca_topic_score_gemma":0.0001769741,"domain_scores_codex":[0.9991668,0.00004232058,0.0002139116,0.0001709522,0.0001644838,0.0002415525],"domain_scores_gemma":[0.9993723,0.00004505449,0.00002907726,0.0004490979,0.00003361921,0.00007084997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009121229,0.000118943,0.04252021,0.0001852188,0.001814968,0.000003793016,0.001187134,0.9183063,0.01148679,0.003245867,0.000106811,0.02093276],"study_design_scores_gemma":[0.0006536847,0.0002065226,0.006277066,0.00003078315,0.0001659268,0.000005405133,0.0003392296,0.8470299,0.1395906,0.00008825473,0.00518457,0.0004280277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8425044,0.00001082883,0.1106394,0.0001310466,0.00002665648,0.0001117967,0.000001020241,0.0004412332,0.0461336],"genre_scores_gemma":[0.9968445,0.000006186034,0.002370697,0.0001691796,0.00005092492,0.00002130939,0.00001589057,0.00002962905,0.0004917106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1543401,"threshold_uncertainty_score":0.4745688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0150035947837455,"score_gpt":0.215553150767715,"score_spread":0.2005495559839695,"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."}}