{"id":"W3022491056","doi":"","title":"Seasonal Mass Balance and Balance Gradients from Airborne Laser Altimetry, Columbia River Basin, Canada.","year":2016,"lang":"en","type":"article","venue":"AGUFM","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Satellite altimetry; Altimeter; Drainage basin; Environmental science; Balance (ability); Climatology; Geology; Hydrology (agriculture); Geography; Remote sensing; Cartography","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":[0.0002545959,0.0003500141,0.0002685527,0.001232878,0.001770723,0.0009552908,0.0008789381,0.000451359,0.003275807],"category_scores_gemma":[0.0007146843,0.0002929179,0.0002195105,0.003919536,0.0004459815,0.0004007562,0.0004432254,0.0005657274,0.0005079623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01328931,"about_ca_system_score_gemma":0.01838304,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9967943,"about_ca_topic_score_gemma":0.9985378,"domain_scores_codex":[0.9998191,0.000007978457,0.000008869886,0.00004340723,0.00008006053,0.00004060181],"domain_scores_gemma":[0.9995829,0.00001932186,0.00002849849,0.0000163748,0.0003088969,0.00004405924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003822207,0.0001433463,0.8566297,0.0002391463,0.0002581725,0.0002252897,0.001098129,0.01042215,0.008032392,0.001069081,0.05160484,0.06989554],"study_design_scores_gemma":[0.00002421674,0.000005517516,0.987211,0.00003120643,0.00003883259,0.00001891914,0.0005056949,0.003217958,0.0005738718,0.0001075327,0.008245184,0.00002004474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9032395,0.001900697,0.0009924256,0.001144962,0.00007295705,0.00006810282,0.07304367,0.0003932379,0.01914445],"genre_scores_gemma":[0.9765751,0.0004736609,0.001373586,0.00009612144,0.000008577022,0.00002927512,0.01348237,0.00007128038,0.007890073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01328931,"threshold_uncertainty_score":0.09642112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002789159179320122,"score_gpt":0.1580336508064515,"score_spread":0.1552444916271313,"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."}}