{"id":"W4249584550","doi":"10.31223/osf.io/4qtxj","title":"Lessons learned from monitoring of turbidity currents and guidance for future platform designs","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"U.S. Geological Survey; Ocean University of China; Natural Environment Research Council; Sight Research UK","keywords":"Turbidity current; Mooring; Environmental science; Marine engineering; Seafloor spreading; Computer science; Geology; Remote sensing; Engineering; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.006691479,0.001844755,0.0007958683,0.0009780906,0.0009018463,0.00314835,0.003248062,0.003443616,0.005339638],"category_scores_gemma":[0.01369733,0.0005743536,0.0005851698,0.0006545042,0.001846615,0.007072483,0.002040646,0.003414984,0.002668871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001248453,"about_ca_system_score_gemma":0.002238494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007961818,"about_ca_topic_score_gemma":0.01117844,"domain_scores_codex":[0.9968904,0.001073278,0.0001840273,0.0004674387,0.001145197,0.0002395451],"domain_scores_gemma":[0.9906937,0.002766854,0.0004089122,0.001355024,0.004011156,0.0007644448],"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":[0.0001736941,0.0002351348,0.01309818,0.001465616,0.00006476069,0.0008954434,0.001576786,0.08720948,0.01915495,0.0357197,0.03839342,0.8020128],"study_design_scores_gemma":[0.0001368448,0.001064112,0.01408226,0.003162915,0.0001532935,0.001412689,0.008385256,0.1679754,0.03521189,0.1991738,0.5688087,0.0004329651],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06183254,0.02249939,0.7833911,0.07438617,0.0020081,0.0003721752,0.0007799079,0.003652619,0.0510781],"genre_scores_gemma":[0.2996491,0.01504163,0.666381,0.003405745,0.0004860108,0.0002811088,0.0006520293,0.0005954548,0.01350789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007961818,"threshold_uncertainty_score":0.03538841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2550215590300521,"score_gpt":0.3388520659961174,"score_spread":0.08383050696606537,"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."}}