{"id":"W4296510886","doi":"10.5750/ijme.v164i1.18","title":"Ice Sensing Technologies with Applications in Augmented Situational Awareness","year":2022,"lang":"en","type":"article","venue":"The International Journal of Maritime Engineering","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Situation awareness; Sea ice; Situational ethics; Computer science; Operations research; Meteorology; Engineering; Geography; Psychology; 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":[0.0007510948,0.0007929564,0.0004317932,0.002763682,0.0003662416,0.002244509,0.0006993592,0.001194904,0.003438001],"category_scores_gemma":[0.001310849,0.0003627975,0.0005893256,0.00353839,0.0006268026,0.001900097,0.001130838,0.0007318384,0.001326482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003305259,"about_ca_system_score_gemma":0.0003864296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001587784,"about_ca_topic_score_gemma":0.001847073,"domain_scores_codex":[0.9993634,0.0001052416,0.0000422669,0.0001196512,0.0003259385,0.00004355502],"domain_scores_gemma":[0.9991933,0.0003484099,0.00008198596,0.00008827187,0.0002622925,0.00002581392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001509677,0.0001012363,0.002885144,0.002980756,0.0001551293,0.0005667364,0.0007787485,0.0155824,0.05282854,0.02366867,0.01649407,0.8838077],"study_design_scores_gemma":[0.0000522351,0.0005855206,0.01332047,0.002243855,0.0003939738,0.003132605,0.001579414,0.09337672,0.0735969,0.07248567,0.7388487,0.0003839449],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0234163,0.1338785,0.7587181,0.002311881,0.001982421,0.0003280747,0.001988542,0.002631112,0.07474497],"genre_scores_gemma":[0.3336918,0.1315491,0.5109907,0.001688067,0.0017772,0.000377549,0.002745905,0.0003186424,0.01686097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003438001,"threshold_uncertainty_score":0.01150125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006133134233748579,"score_gpt":0.1945712535667831,"score_spread":0.1884381193330346,"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."}}