{"id":"W2612945519","doi":"","title":"Snow Water Equivalent Estimation Using Blackbox Optimization","year":2011,"lang":"en","type":"article","venue":"Les Cahiers du GERAD","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kriging; Interpolation (computer graphics); Computer science; Set (abstract data type); Snow; Mathematical optimization; Algorithm; Data mining; Machine learning; Mathematics; Artificial intelligence; Meteorology","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":[0.0008326775,0.0006029837,0.0009941818,0.0004124191,0.0003557341,0.0008309298,0.000790248,0.0009504998,0.002454955],"category_scores_gemma":[0.0024241,0.0004294255,0.0005370106,0.0003072681,0.0006081568,0.0006244013,0.0008225651,0.0004843818,0.0002562321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005784188,"about_ca_system_score_gemma":0.001050532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0116706,"about_ca_topic_score_gemma":0.006806329,"domain_scores_codex":[0.9997749,0.0001098111,0.000008809305,0.00003742132,0.00004058929,0.0000284989],"domain_scores_gemma":[0.9989901,0.0006872551,0.00009978054,0.0000628152,0.0001166976,0.0000433356],"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":[0.00002081702,0.000006428715,0.0001846149,0.000005893967,0.000006006685,0.000009570047,0.000006259644,0.9974483,0.000262654,0.0004002189,0.00004487934,0.001604425],"study_design_scores_gemma":[0.000004025173,0.000004352283,0.00002056856,8.856513e-7,6.367194e-7,6.640165e-7,0.00000181234,0.9996325,0.0001061365,0.0001902485,0.00003743323,6.373974e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1786195,0.0001025393,0.8137671,0.0002085931,0.00003092498,0.0001122011,0.0002890725,0.00070843,0.006161501],"genre_scores_gemma":[0.8535132,0.0000623376,0.1432765,0.00007614141,0.000009038313,0.0001894281,0.0002639675,0.00011551,0.002493765],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0116706,"threshold_uncertainty_score":0.02320534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04037595506049975,"score_gpt":0.2090440136102995,"score_spread":0.1686680585497998,"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."}}