{"id":"W2095752931","doi":"10.1139/cjce-2014-0412","title":"Steep channel freezeup processes: understanding complexity with statistical and physical models","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Channel (broadcasting); Process (computing); Geology; Dominance (genetics); Hydrology (agriculture); Environmental science; Computer science; Geotechnical engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0008449495,0.0005081936,0.0008628889,0.0008206481,0.0005837,0.001405252,0.00100499,0.0009152488,0.001043093],"category_scores_gemma":[0.003653186,0.0004808705,0.001030515,0.0005629585,0.001072515,0.002956376,0.0009246653,0.001101189,0.0001409737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001261274,"about_ca_system_score_gemma":0.001217786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02117649,"about_ca_topic_score_gemma":0.01274748,"domain_scores_codex":[0.9998425,0.00005678184,0.00001079538,0.00002647891,0.0000337197,0.00002964941],"domain_scores_gemma":[0.9980888,0.001269787,0.0002972859,0.0001573082,0.00009539235,0.00009134028],"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":[0.00001144052,0.00003438018,0.004188557,0.00002695671,0.00003913771,0.0000381183,0.00007254827,0.9737659,0.0003595051,0.01780739,0.0003081319,0.003348043],"study_design_scores_gemma":[0.000002390405,0.000004589086,0.0007041438,0.000003573022,0.000004339012,0.000006993017,0.00001655709,0.9837235,0.00003464752,0.01526399,0.0002289357,0.000006239133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5294169,0.00204322,0.4544427,0.002589588,0.00008163415,0.0001253528,0.0008508072,0.000531968,0.009917923],"genre_scores_gemma":[0.9679869,0.001778599,0.02783953,0.0001108924,0.0001371018,0.0001588024,0.0002652303,0.00009073555,0.001632236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02117649,"threshold_uncertainty_score":0.04210645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04377384119006621,"score_gpt":0.2058941806203876,"score_spread":0.1621203394303214,"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."}}