{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001068263,0.0001004374,0.00009852085,0.00002611837,0.0003945396,0.00003410274,0.00008754303,0.00006095821,0.003538724],"category_scores_gemma":[0.00002658082,0.00007374033,0.00004269409,0.0001119981,0.0000958413,0.0002032884,0.000008356276,0.00007363751,0.00008676104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001343624,"about_ca_system_score_gemma":0.00001016912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001369116,"about_ca_topic_score_gemma":0.0001672292,"domain_scores_codex":[0.9993117,0.00002698561,0.0001577863,0.000158472,0.0001281908,0.0002168412],"domain_scores_gemma":[0.9997146,0.00003111226,0.00004328486,0.000114322,0.00004040749,0.00005630059],"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":[0.00005264378,0.00004445158,0.1668669,0.00002854672,0.0000726924,0.00002305349,0.01266738,0.7822838,0.00005291764,0.001548085,0.0006900131,0.03566954],"study_design_scores_gemma":[0.0002630585,0.00007035715,0.1342412,0.00001307822,0.00004823314,0.00001367491,0.0008622551,0.8606088,0.0003343458,0.001655998,0.001639499,0.0002494987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7966171,0.0001577482,0.1996709,0.000187229,0.0004875306,0.0001344856,0.00001219878,0.00006318526,0.002669665],"genre_scores_gemma":[0.8511656,0.00008685897,0.1479919,0.000264208,0.0001114811,0.000001313833,0.0001304864,0.000005329561,0.0002428929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07832499,"threshold_uncertainty_score":0.9973722,"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."}}