{"id":"W2559101150","doi":"10.4043/27364-ms","title":"Probabilistic Assessment of Multi-Year Sea Ice Loads on Upward Sloping Arctic Structures","year":2016,"lang":"en","type":"article","venue":"Arctic Technology Conference","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering","funders":"","keywords":"Monte Carlo method; Randomness; Probabilistic logic; Calibration; Sea ice; Ridge; Extreme value theory; Computer science; Probability distribution; Geology; Mathematics; Statistics; Climatology","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":[0.001416013,0.0004194734,0.0003037242,0.0008555909,0.0002987498,0.000584546,0.0005054139,0.0004653455,0.000693424],"category_scores_gemma":[0.002586965,0.0003758554,0.0005992302,0.0005272412,0.0003691452,0.000523339,0.0004757677,0.0002378499,0.0000864726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017125,"about_ca_system_score_gemma":0.0004494112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01127444,"about_ca_topic_score_gemma":0.009027977,"domain_scores_codex":[0.9996057,0.0001656571,0.00001856743,0.00004870364,0.0001152277,0.000046085],"domain_scores_gemma":[0.998576,0.0009067424,0.0001635123,0.00008293032,0.000220212,0.00005047725],"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":[0.00002698513,0.000009771857,0.008001845,0.000005598676,0.00001135161,0.00002147076,0.00001017334,0.989824,0.0004856615,0.0002457477,0.00001851215,0.001338984],"study_design_scores_gemma":[0.000001656402,0.00003292026,0.00420568,0.000001657689,0.000005301131,0.000007293193,0.00001299369,0.9949436,0.0005752524,0.0001657405,0.00004352405,0.000004498686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9656144,0.00003822742,0.03243954,0.00002584678,0.00000373451,0.00003198016,0.000235,0.0001107263,0.001500735],"genre_scores_gemma":[0.9980991,0.00001163291,0.001677458,0.000001601867,9.126687e-7,0.000009486339,0.00007130847,0.000004814302,0.0001235743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01127444,"threshold_uncertainty_score":0.02241766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01992528556087989,"score_gpt":0.2529674081968782,"score_spread":0.2330421226359984,"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."}}