{"id":"W4366777253","doi":"10.4043/32591-ms","title":"Advances in Satellite Technology for Ice Management","year":2023,"lang":"en","type":"article","venue":"Offshore Technology Conference","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering","funders":"","keywords":"Sea ice; Satellite; Remote sensing; Earth observation; Environmental science; Iceberg; Computer science; Meteorology; Geology; Oceanography; Engineering; Geography; Aerospace engineering","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":[0.001717948,0.0005311516,0.0003421858,0.00146534,0.0003578927,0.001476626,0.0006388342,0.0006987466,0.01374264],"category_scores_gemma":[0.001690394,0.0002121817,0.0004619434,0.001946996,0.0005057066,0.001803371,0.001025129,0.001321504,0.004835891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009811925,"about_ca_system_score_gemma":0.001006005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002995494,"about_ca_topic_score_gemma":0.002371022,"domain_scores_codex":[0.9991579,0.0002466544,0.00005381366,0.00009920348,0.0004004066,0.00004196167],"domain_scores_gemma":[0.9984983,0.0003328756,0.00009973256,0.0001785005,0.0008240097,0.00006648628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008759876,0.00008162922,0.003335857,0.0006969826,0.00004780404,0.0001729383,0.0003217413,0.005281501,0.02738417,0.07911742,0.04583858,0.8376337],"study_design_scores_gemma":[0.00001990924,0.0001354906,0.002329249,0.0004488229,0.0000407654,0.0003826312,0.0001830763,0.008335382,0.01126997,0.01878819,0.9580224,0.00004419551],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03766971,0.2188557,0.3996143,0.02726577,0.008378849,0.0004184307,0.001648777,0.002929451,0.303219],"genre_scores_gemma":[0.2523753,0.1820427,0.4499766,0.004372589,0.008457486,0.0003013987,0.002184395,0.0006830516,0.09960641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01374264,"threshold_uncertainty_score":0.04597378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01227597070599511,"score_gpt":0.2407602466367675,"score_spread":0.2284842759307724,"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."}}