{"id":"W6889564197","doi":"10.26022/ieda/317435","title":"Processed ship-based Multibeam Sonar Data (version 2) acquired along the Peru-Chile Trench during the Knorr expedition KN182-08 (2005)","year":2011,"lang":"en","type":"dataset","venue":"LDEO - Lamont-Doherty Earth Observatory, Columbia University","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sonar; Backscatter (email); Data set; Trench; Synthetic aperture sonar; Seabed","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005099844,0.001038749,0.0006367441,0.002503555,0.0005144427,0.0008815276,0.001442426,0.0007623959,0.009984786],"category_scores_gemma":[0.001202495,0.0004756239,0.00052024,0.004046288,0.0002865936,0.0005580253,0.0009511449,0.0008617284,0.0160695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001319531,"about_ca_system_score_gemma":0.001858742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1072735,"about_ca_topic_score_gemma":0.1836685,"domain_scores_codex":[0.9995764,0.00003774424,0.00003602543,0.0001098681,0.0001494619,0.00009058468],"domain_scores_gemma":[0.9992955,0.00006204494,0.00008995009,0.0001662351,0.00032827,0.00005801857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000197588,0.00009836711,0.01202335,0.0006601867,0.00008195853,0.0001371241,0.0001853809,0.002409382,0.00120073,0.0005677678,0.9693856,0.01305258],"study_design_scores_gemma":[0.0001290212,0.0000252708,0.08140776,0.0002102169,0.00004369927,0.0001253645,0.0004067246,0.001767696,0.002170234,0.0004056252,0.9132465,0.00006198503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002990113,0.00004185488,0.0001886345,0.00004526123,0.00001629984,0.00001934816,0.9950813,0.0003181946,0.001298995],"genre_scores_gemma":[0.002705641,0.00002714035,0.0004515181,0.00001067284,0.000003783538,0.00004986449,0.9954301,0.00005163513,0.001269683],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1072735,"threshold_uncertainty_score":0.2132982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03963271770910255,"score_gpt":0.2165100776506506,"score_spread":0.1768773599415481,"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."}}