{"id":"W311561747","doi":"10.4095/211621","title":"Global Terrestrial Network for Permafrost (GTNet-P): permafrost monitoring contributing to global climate observations","year":2000,"lang":"en","type":"report","venue":"","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Permafrost; Environmental science; Physical geography; Global warming; Climate change; Earth science; Climatology; Geology; Geography; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002165253,0.0008515932,0.0003315997,0.001991952,0.0005218618,0.0007624334,0.001126303,0.0006371104,0.005765246],"category_scores_gemma":[0.00255984,0.0002490871,0.0001925188,0.0036662,0.000201618,0.0008354225,0.0009059972,0.0006035161,0.004236052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001321249,"about_ca_system_score_gemma":0.007015501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1768907,"about_ca_topic_score_gemma":0.1373207,"domain_scores_codex":[0.9992436,0.0001195475,0.00004562426,0.00008890456,0.0004012206,0.0001011468],"domain_scores_gemma":[0.9966381,0.0002887483,0.0002679424,0.0003212692,0.002022659,0.000461228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003395339,0.0002162733,0.09354462,0.0005391391,0.00008881283,0.0002291321,0.0002707346,0.003881099,0.00409895,0.004047569,0.7617532,0.130991],"study_design_scores_gemma":[0.0002165617,0.00009498877,0.1942724,0.0001511491,0.00004399654,0.0002045589,0.0002569177,0.005400166,0.004725985,0.001112303,0.793484,0.00003705354],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.03189332,0.00122841,0.00995751,0.002596829,0.000511764,0.002024328,0.8630651,0.002223435,0.08649919],"genre_scores_gemma":[0.04355166,0.001199604,0.03184235,0.0005049907,0.0001292512,0.001559171,0.8972219,0.0004260114,0.02356516],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1768907,"threshold_uncertainty_score":0.3517222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1078265004628699,"score_gpt":0.3286942668739677,"score_spread":0.2208677664110977,"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."}}