{"id":"W3046360287","doi":"","title":"3D Imaging and Automated Ice Bottom Tracking of Canadian Arctic Archipelago Ice Sounding Data","year":2016,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Sea ice; Arctic; Depth sounding; Archipelago; Geology; Remote sensing; Arctic ice pack; Iceberg; Tracking (education); Cryosphere; Climatology; Sea ice thickness; Oceanography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003896358,0.0005898797,0.0003793936,0.003204432,0.0009396452,0.001148719,0.000705461,0.000564251,0.001939938],"category_scores_gemma":[0.0006877751,0.0004997651,0.0005975748,0.003289623,0.000368038,0.0003445001,0.0006194733,0.0004730677,0.001083075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00212302,"about_ca_system_score_gemma":0.00589913,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7591903,"about_ca_topic_score_gemma":0.8977503,"domain_scores_codex":[0.9995618,0.000015494,0.00001371593,0.00008130735,0.0002111538,0.0001164891],"domain_scores_gemma":[0.9994336,0.00004523284,0.00003109374,0.00006021135,0.000383879,0.00004602576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006846727,0.0004324839,0.1478963,0.000381436,0.0003216741,0.0007780856,0.001257603,0.1226567,0.1941041,0.001203701,0.03266417,0.4976191],"study_design_scores_gemma":[0.00005640555,0.00004057593,0.4960845,0.00006254681,0.0001069922,0.0001769493,0.0006620581,0.4511131,0.02916447,0.0003464801,0.02207387,0.0001120124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9086097,0.000841765,0.03261122,0.0003721759,0.0002124813,0.0002251332,0.04185554,0.005075205,0.01019679],"genre_scores_gemma":[0.8640932,0.0006042095,0.08628356,0.0001068588,0.00005275666,0.0001352011,0.04194057,0.0004540417,0.006329634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2408097,"threshold_uncertainty_score":0.4844557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02354526494758598,"score_gpt":0.2444512971064104,"score_spread":0.2209060321588245,"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."}}