{"id":"W1979552197","doi":"10.1016/s0165-232x(03)00067-3","title":"Snowpack properties for snow profile analysis","year":2003,"lang":"en","type":"article","venue":"Cold Regions Science and Technology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":124,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Chinese Academy of Agricultural Sciences","keywords":"Snowpack; Snow; Univariate; Multivariate statistics; Multivariate analysis; Environmental science; Stability (learning theory); Layer (electronics); Geology; Geotechnical engineering; Statistics; Mathematics; Materials science; Composite material; Computer science; Geomorphology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002772583,0.00007750457,0.0001429003,0.0002460008,0.0008852623,0.0000500485,0.0002055836,0.00005581171,0.00009100814],"category_scores_gemma":[0.0005064831,0.00005586633,0.00003202216,0.004063376,0.001212368,0.0001369189,0.00001646876,0.00005421936,0.00001182572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006067033,"about_ca_system_score_gemma":0.0001361344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008760108,"about_ca_topic_score_gemma":0.0009144396,"domain_scores_codex":[0.9991491,0.000007391714,0.0001108007,0.0002957083,0.0001357327,0.0003012854],"domain_scores_gemma":[0.9994091,0.00005155234,0.00004261335,0.000213999,0.0002264979,0.00005619265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001022003,0.00005598871,0.7409211,0.00002384135,0.0001577335,0.000003731984,0.000313462,0.00035017,0.001479547,0.2217201,0.007408387,0.02755568],"study_design_scores_gemma":[0.0008104108,0.000729562,0.1920613,0.00003506412,0.0004886583,0.00003518115,0.009027314,0.03476824,0.009886514,0.01570147,0.7356445,0.0008118362],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737809,0.004087298,0.003677274,0.009539258,0.0003301675,0.0009275798,0.00003720387,0.0002256253,0.007394707],"genre_scores_gemma":[0.9952719,0.000162478,0.003369522,0.000136924,0.00001056756,0.00001496287,0.000002863363,0.000001368553,0.001029417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7282361,"threshold_uncertainty_score":0.6808811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03084587358359358,"score_gpt":0.2236601237348715,"score_spread":0.1928142501512779,"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."}}