{"id":"W2172335393","doi":"","title":"The InterFrost benchmark of Thermo-Hydraulic codes for cold regions hydrology - first inter-comparison results","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université de Montréal","funders":"","keywords":"Permafrost; Context (archaeology); Environmental science; Climate change; Benchmark (surveying); Hydrology (agriculture); Groundwater; Computer science; Geology; Geotechnical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017588,0.0008080201,0.0006735123,0.0007934474,0.0006195362,0.0008537791,0.001638882,0.0008985886,0.005035684],"category_scores_gemma":[0.00437626,0.00027801,0.0007851458,0.001087812,0.00054607,0.001805863,0.0009451448,0.001086972,0.001010174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008279431,"about_ca_system_score_gemma":0.001423595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03055719,"about_ca_topic_score_gemma":0.03403315,"domain_scores_codex":[0.9992417,0.000221388,0.00005009277,0.0001398857,0.0002275768,0.0001192496],"domain_scores_gemma":[0.9968849,0.001031785,0.000117355,0.0007623833,0.0009388477,0.0002646902],"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":[0.003033254,0.001296576,0.03650241,0.0004271864,0.0004127141,0.0001891036,0.0002253521,0.824585,0.01023323,0.006836633,0.04838994,0.06786866],"study_design_scores_gemma":[0.001176279,0.0008951145,0.04285726,0.00005844973,0.0001171016,0.00007473519,0.0002377579,0.9164811,0.01851097,0.005865542,0.01362407,0.0001015077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9293399,0.0008314273,0.01110211,0.0005693836,0.0003280683,0.0001025532,0.02665308,0.006214804,0.02485867],"genre_scores_gemma":[0.9513363,0.0001402028,0.012495,0.0001879036,0.00006688043,0.00008274523,0.03141941,0.00126883,0.003002733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03055719,"threshold_uncertainty_score":0.06075865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04254671653952267,"score_gpt":0.2591125601345761,"score_spread":0.2165658435950534,"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."}}