{"id":"W2142965673","doi":"10.14430/arctic4426","title":"Using Synthetic Aperture Radar to Define Spring Breakup on the Kuparuk River, Northern Alaska","year":2014,"lang":"en","type":"article","venue":"ARCTIC","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alaska Climate Adaptation Science Center, University of Alaska Fairbanks; Office of Experimental Program to Stimulate Competitive Research; National Aeronautics and Space Administration","keywords":"Remote sensing; Synthetic aperture radar; Arctic; Environmental science; Surface runoff; Breakup; Satellite imagery; Geology; Oceanography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0004901598,0.0001893101,0.0001378435,0.0007524284,0.0002460634,0.0005152752,0.0001417343,0.0001348253,0.0002371692],"category_scores_gemma":[0.0008486378,0.00008235379,0.0001209134,0.0005110243,0.0002230911,0.0002826058,0.0002308443,0.0001299447,0.0000704585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003504971,"about_ca_system_score_gemma":0.000337972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02806964,"about_ca_topic_score_gemma":0.05812923,"domain_scores_codex":[0.9998754,0.00002762813,0.00001538772,0.00003495215,0.00002617985,0.00002034421],"domain_scores_gemma":[0.9995499,0.0001403598,0.0001380711,0.00002742436,0.00009954943,0.00004461293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001417367,0.00006357915,0.9744692,0.00001742354,0.00003223058,0.00009243411,0.0004280667,0.003780061,0.007195131,0.00004354207,0.00005545372,0.01368118],"study_design_scores_gemma":[0.00000175198,0.00005722413,0.9923322,0.000005591652,0.00001564385,0.00002623191,0.0008328404,0.005502734,0.001024559,0.00002408905,0.0001725583,0.000004514197],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996274,0.00002093173,0.0001815464,0.000002220451,7.066623e-7,0.000002468513,0.00004358181,0.000002960255,0.000118196],"genre_scores_gemma":[0.9990813,0.00003208998,0.0005427607,0.000001707713,0.000001079839,0.000003835911,0.0002129424,0.00000124546,0.0001231721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02806964,"threshold_uncertainty_score":0.05581254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02769001598946374,"score_gpt":0.2110972656382115,"score_spread":0.1834072496487477,"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."}}