{"id":"W2800495075","doi":"10.1029/2018gl077676","title":"Using Vertically Integrated Ocean Fields to Characterize Greenland Icebergs' Distribution and Lifetime","year":2018,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Polar Knowledge Canada","keywords":"Iceberg; Oceanography; Geology; Buoyancy; Keel; Water mass; Climatology; Ocean current; Sea ice","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002981383,0.000398885,0.0001899953,0.0004464184,0.0001803981,0.0007406697,0.0003831877,0.0003371914,0.0003773762],"category_scores_gemma":[0.0008803366,0.0001809605,0.0003286848,0.000478769,0.0002666713,0.0006768735,0.0003102619,0.0002270687,0.00005074479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001483839,"about_ca_system_score_gemma":0.0007329293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1351694,"about_ca_topic_score_gemma":0.07195198,"domain_scores_codex":[0.9999362,0.00001308889,0.000005111459,0.00002306972,0.000006269795,0.00001619447],"domain_scores_gemma":[0.9997746,0.00006330237,0.00005025484,0.00003191968,0.00005031268,0.0000295579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00009915169,0.00006918603,0.1955729,0.00001172618,0.0001016052,0.00006228772,0.00005439737,0.7931887,0.003743907,0.000557275,0.0002650599,0.006273887],"study_design_scores_gemma":[0.00002059073,0.00002555426,0.07984466,0.000006860992,0.00002109805,0.000009384056,0.00005432471,0.9185119,0.0009051973,0.0003773561,0.0002080151,0.00001501598],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976438,0.00002426587,0.00138882,0.00003201815,0.000004537806,0.000004152094,0.0004293867,0.00005039954,0.0004226906],"genre_scores_gemma":[0.9987831,0.00001602458,0.0006402072,0.000009680604,0.000001435445,0.000002524024,0.0004410269,0.000007214729,0.00009883863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1351694,"threshold_uncertainty_score":0.2687652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03340959684763919,"score_gpt":0.2845277031735661,"score_spread":0.2511181063259269,"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."}}