{"id":"W2803109927","doi":"","title":"Permafrost response to climate change: Linking field observation with numerical simulation","year":2013,"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":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; McGill University; Université de Montréal; University of Calgary","funders":"","keywords":"Permafrost; Climate change; Field (mathematics); Environmental science; Computer simulation; Climatology; Remote sensing; Geology; Meteorology; Computer science; Simulation; Oceanography; Geography; Mathematics","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":[0.0009564967,0.000242017,0.0004596721,0.0005863481,0.0003736198,0.001399089,0.0006785968,0.001328586,0.002289756],"category_scores_gemma":[0.004678475,0.0003645965,0.0005276497,0.001129362,0.0004161633,0.001249168,0.000520687,0.0004429304,0.0002868035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008688631,"about_ca_system_score_gemma":0.000825136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04283891,"about_ca_topic_score_gemma":0.02314673,"domain_scores_codex":[0.9996907,0.0001118585,0.00002363818,0.0001026952,0.00004337625,0.00002784238],"domain_scores_gemma":[0.9985624,0.0008500027,0.0001454195,0.0002226994,0.0001580206,0.00006143497],"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":[0.0003799113,0.0004969947,0.1700798,0.0001832768,0.0003730923,0.00009674365,0.0002303674,0.7751393,0.007473133,0.001692907,0.00237709,0.04147734],"study_design_scores_gemma":[0.00004755255,0.00002836945,0.06149187,0.00001911349,0.0000300235,0.00001372724,0.00008384839,0.934039,0.001459514,0.00190713,0.0008514823,0.00002839392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808348,0.0002303132,0.01149776,0.0006609915,0.0000773014,0.00004236555,0.002152781,0.0004629524,0.004040697],"genre_scores_gemma":[0.9944517,0.00008902363,0.004348,0.00004573401,0.00002238578,0.00002525797,0.0006861777,0.00003784522,0.000293895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04283891,"threshold_uncertainty_score":0.08517909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04596903380731237,"score_gpt":0.2576219265211521,"score_spread":0.2116528927138397,"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."}}