{"id":"W2551863608","doi":"10.5194/essd-9-317-2017","title":"PeRL: a circum-Arctic Permafrost Region Pond and Lake database","year":2017,"lang":"en","type":"article","venue":"Earth system science data","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut National de la Recherche Scientifique","funders":"","keywords":"Permafrost; Arctic; Tundra; Thermokarst; Physical geography; Ecoregion; Wetland; Environmental science; Boreal; Hydrology (agriculture); Database; Geology; Oceanography; Ecology; Geography","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":[0.0007604735,0.0009691092,0.0008833101,0.004015126,0.0005481147,0.001281758,0.001481052,0.0005657562,0.0177558],"category_scores_gemma":[0.002114691,0.0003614002,0.0004955017,0.006889217,0.0001771795,0.001528539,0.001360882,0.0004963973,0.01697906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008884768,"about_ca_system_score_gemma":0.002050858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03556629,"about_ca_topic_score_gemma":0.05000049,"domain_scores_codex":[0.9994586,0.00006542879,0.00008751567,0.0001614299,0.0001661586,0.0000606986],"domain_scores_gemma":[0.9989845,0.0001181281,0.0001786444,0.0001730725,0.0004244475,0.0001212477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003182571,0.00006004509,0.01353795,0.001510002,0.0001642877,0.0002059242,0.000200827,0.001683107,0.001235214,0.001845126,0.9491283,0.03011104],"study_design_scores_gemma":[0.000419666,0.00005118951,0.05507054,0.0004094662,0.0001290459,0.0002479804,0.0003358036,0.008197549,0.002073992,0.002372144,0.9306017,0.00009090094],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00241645,0.0001588409,0.0007015116,0.00004316251,0.000007471641,0.00003839041,0.9930584,0.001535001,0.002040693],"genre_scores_gemma":[0.003029891,0.0000734249,0.001958434,0.00002128641,0.000003547819,0.0001270704,0.9943025,0.0001156937,0.0003681505],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03556629,"threshold_uncertainty_score":0.07071859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1109094805208814,"score_gpt":0.2910291341862095,"score_spread":0.1801196536653281,"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."}}