{"id":"W4323662617","doi":"10.1029/2022ms003013","title":"Challenges in Hydrologic‐Land Surface Modeling of Permafrost Signatures—A Canadian Perspective","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada; University of Saskatchewan","keywords":"Permafrost; Forcing (mathematics); Environmental science; Surface runoff; Climatology; Radiative forcing; Identifiability; Climate model; Climate change; Computer science; Meteorology; Geology; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001391394,0.0001719339,0.0005043568,0.0006257599,0.00006185734,0.00003374678,0.0002780089,0.0001276694,0.00004859954],"category_scores_gemma":[0.00008945881,0.0001407123,0.00008581881,0.0004591816,0.00003184699,0.0005373508,0.00001087351,0.0004304879,0.00001323746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003334984,"about_ca_system_score_gemma":0.000153585,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09669174,"about_ca_topic_score_gemma":0.6927895,"domain_scores_codex":[0.9980648,0.0001484903,0.0007150768,0.0002323973,0.0003856534,0.0004536525],"domain_scores_gemma":[0.9990773,0.0001704943,0.0002383146,0.0001441308,0.0002052995,0.0001644594],"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":[0.0000586896,0.000007951192,0.1196064,0.00006525223,0.000007614864,0.0001184452,0.00222887,0.8775307,0.00004756406,0.00001965686,0.000004030228,0.0003048296],"study_design_scores_gemma":[0.0003897218,0.0001307644,0.006120344,0.0004302275,0.000005807623,0.00005158928,0.008889748,0.9830958,0.000002996793,0.000609102,0.0001217151,0.0001521909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9127486,0.083395,0.0000662769,0.0003375206,0.0008115895,0.0001574699,0.0004016288,0.00001019338,0.002071767],"genre_scores_gemma":[0.965691,0.03396112,0.0000647112,0.00002503668,0.0001888974,4.984323e-7,0.00005129696,0.000007391517,0.00001002716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5960978,"threshold_uncertainty_score":0.9093235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08101649676901311,"score_gpt":0.2867544564053057,"score_spread":0.2057379596362925,"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."}}