{"id":"W2889241192","doi":"10.1002/ppp.1986","title":"Thermokarst pond dynamics in subarctic environment monitoring with radar remote sensing","year":2018,"lang":"en","type":"article","venue":"Permafrost and Periglacial Processes","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université Laval; Center for Northern Studies","funders":"Canadian Space Agency; Bayerische Forschungsallianz","keywords":"Thermokarst; Permafrost; Subarctic climate; Geology; Environmental science; Hydrology (agriculture); Geomorphology; Remote sensing; Physical geography; Soil science; Geotechnical engineering; Oceanography; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002987418,0.0001447187,0.000146601,0.0009834723,0.0001324891,0.0002718579,0.0001198201,0.0001137286,0.0005321288],"category_scores_gemma":[0.0002864152,0.00009633086,0.00011645,0.0007213909,0.0001488124,0.0003068112,0.0002533372,0.0000957685,0.0001250923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002177225,"about_ca_system_score_gemma":0.0001367296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007243564,"about_ca_topic_score_gemma":0.01621686,"domain_scores_codex":[0.9999211,0.00001760581,0.000004455922,0.0000231428,0.00001812857,0.00001565938],"domain_scores_gemma":[0.999772,0.00003957665,0.0000913543,0.00001987517,0.00005195084,0.0000252154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009285376,0.00004624418,0.9514916,0.000058345,0.00005481209,0.0002035877,0.0002529683,0.002742277,0.02173666,0.00005007594,0.0001524168,0.02311816],"study_design_scores_gemma":[0.000002298772,0.00002497213,0.9943795,0.000005946746,0.00001455023,0.0000724918,0.0001252839,0.003975437,0.001176604,0.00001944025,0.0002003459,0.000003168871],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986668,0.0001258958,0.0004530802,0.00000830597,0.00000134539,0.000003545588,0.0002110118,0.00002819914,0.0005019174],"genre_scores_gemma":[0.9985256,0.00008487194,0.001079048,0.000004204722,0.000002153023,0.000002871717,0.0001637607,0.000002145617,0.000135495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007243564,"threshold_uncertainty_score":0.01440281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035773453736395,"score_gpt":0.2273656341812521,"score_spread":0.2070078996438881,"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."}}