{"id":"W4366778416","doi":"10.4043/32372-ms","title":"SIIBED: An Updated Subsea Iceberg Risk Model for the Grand Banks","year":2023,"lang":"en","type":"article","venue":"Offshore Technology Conference","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering","funders":"","keywords":"Subsea; Iceberg; Sink (geography); Risk model; Marine engineering; Oceanography; Engineering; Geology; Risk analysis (engineering); Geography; Business; Cartography","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":[0.001302074,0.0007922344,0.0007238897,0.000796391,0.0007718605,0.002403082,0.00236752,0.00117934,0.005015655],"category_scores_gemma":[0.002706896,0.0006645914,0.001044179,0.0006201587,0.0005697287,0.001612102,0.001508431,0.001494997,0.0008963204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003405963,"about_ca_system_score_gemma":0.003987128,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09446116,"about_ca_topic_score_gemma":0.04611394,"domain_scores_codex":[0.9994441,0.0001533114,0.00003420341,0.00009308257,0.0002066687,0.00006859166],"domain_scores_gemma":[0.9991699,0.0002135634,0.00007894523,0.00007059194,0.0003843906,0.00008260798],"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":[0.00002358389,0.00001110015,0.001338233,0.00001045966,0.00001581476,0.00004955013,0.00003128278,0.9832454,0.0002989966,0.01002243,0.001618095,0.003335076],"study_design_scores_gemma":[0.00001158976,0.000009619795,0.0002915766,0.0000103551,0.00001102713,0.0000174307,0.00002022046,0.9910355,0.0002299901,0.004173105,0.004175796,0.00001385747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.16161,0.0003673181,0.757743,0.001782509,0.0003008718,0.0002897363,0.005566572,0.001446807,0.07089324],"genre_scores_gemma":[0.8290881,0.0004883963,0.1262208,0.0002327264,0.00008588785,0.0005231359,0.003402319,0.0005312256,0.03942747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9055389,"threshold_uncertainty_score":0.1878226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02316551715026262,"score_gpt":0.2384562147026427,"score_spread":0.2152906975523801,"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."}}