{"id":"W4309218549","doi":"10.5194/hess-2022-279-rc3","title":"Comment on hess-2022-279","year":2022,"lang":"en","type":"peer-review","venue":"","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Aurora Research Institute","keywords":"Thermokarst; Tundra; Snowmelt; Precipitation; Environmental science; Permafrost; Snow; Hydrology (agriculture); Surface runoff; Watershed; Water balance; Arctic; Soil water; Physical geography; Geology; Geography; Oceanography; Soil science; Ecology; Geomorphology; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001401542,0.0008569898,0.0008128246,0.001134604,0.001637919,0.004471603,0.001773339,0.01092988,0.1870328],"category_scores_gemma":[0.00611195,0.0004195947,0.001198558,0.002011406,0.0008869953,0.002320081,0.001808451,0.006643139,0.1221207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002581869,"about_ca_system_score_gemma":0.004241023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02911618,"about_ca_topic_score_gemma":0.02672621,"domain_scores_codex":[0.9987878,0.0001268358,0.00009713818,0.0001598691,0.0005704262,0.0002578504],"domain_scores_gemma":[0.9976996,0.0005311097,0.00008014736,0.0003393815,0.001101797,0.0002480252],"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":[0.00002863597,0.000004664612,0.00007669854,0.00006091978,0.000002547078,0.00007510753,0.000009778076,0.00005115933,0.00007297578,0.001311624,0.99504,0.003265897],"study_design_scores_gemma":[0.000009493517,0.000003558908,0.0005576916,0.00005224099,0.000002141098,0.00002002933,0.00003064656,0.00004207051,0.000106563,0.0006842428,0.998481,0.00001043941],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.001279972,0.002786774,0.001075996,0.2771331,0.2180357,0.0003427047,0.0446165,0.002768817,0.4519605],"genre_scores_gemma":[0.01602817,0.00241997,0.001082994,0.2924948,0.04715138,0.0005586049,0.01811438,0.001138799,0.6210109],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.1870328,"threshold_uncertainty_score":0.625687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2594676846073852,"score_gpt":0.4475464038537151,"score_spread":0.1880787192463299,"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."}}