{"id":"W2558016393","doi":"10.4043/27359-ms","title":"A 3D Time-Domain Model for Iceberg Impacts with Offshore Platforms and Subsea Equipment","year":2016,"lang":"en","type":"article","venue":"Arctic Technology Conference","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering","funders":"Hibernia Management and Development Company","keywords":"Iceberg; Subsea; Submarine pipeline; Marine engineering; Underwater; Field (mathematics); Geology; Engineering; Computer science; Sea ice; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001983053,0.0002199926,0.0002614046,0.0001356124,0.0001952953,0.00002847915,0.0002772119,0.0001768934,0.00031183],"category_scores_gemma":[0.00006586471,0.0001241458,0.00002932056,0.0001518767,0.0006083418,0.000250089,0.0000429325,0.000140951,0.0000646063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002533441,"about_ca_system_score_gemma":0.000177542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001205195,"about_ca_topic_score_gemma":0.0009309734,"domain_scores_codex":[0.9986669,0.00000810129,0.0002020383,0.000402133,0.0001644273,0.000556445],"domain_scores_gemma":[0.9992028,0.0001564433,0.0001062511,0.0002946033,0.00009868603,0.0001412101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000649041,0.00007202777,0.7309867,0.000140025,0.0002061383,0.00004425821,0.0009911129,0.0001430807,0.000999803,0.05664227,0.0001083202,0.2090172],"study_design_scores_gemma":[0.005139287,0.00267147,0.09024127,0.000661662,0.0001903053,0.0006738566,0.002132955,0.4943715,0.0004370965,0.4010793,0.0009779496,0.001423393],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8893678,0.00005400521,0.1046792,0.004410915,0.00003892685,0.0003924838,0.00009100158,0.0001467592,0.0008189318],"genre_scores_gemma":[0.9725614,0.00009582314,0.02650422,0.0002068563,0.00001632341,0.0000133663,0.00002364063,0.000008128052,0.0005702762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6407455,"threshold_uncertainty_score":0.506252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01234475522761083,"score_gpt":0.2050786766733547,"score_spread":0.1927339214457439,"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."}}