{"id":"W4321459044","doi":"10.5194/tc-2022-240","title":"Biogeochemical evolution of ponded meltwater in a High Arctic subglacial tunnel","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Polar Research and Ecology","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta; Natural Resources Canada; Montana State University; National Aeronautics and Space Administration","keywords":"Meltwater; Biogeochemical cycle; Glacier; Arctic; Biogeochemistry; Geology; Oceanography; Permafrost; Hydrology (agriculture); Ecology; Geomorphology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004086721,0.0001328332,0.0002457655,0.0001347394,0.00002089301,0.000009851524,0.000355719,0.0002915567,0.00529972],"category_scores_gemma":[0.0001811463,0.0001171877,0.00008038792,0.0001952658,0.000226951,0.00004968677,0.001762565,0.0004303044,0.001648128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007460951,"about_ca_system_score_gemma":0.00004666343,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05451649,"about_ca_topic_score_gemma":0.02761332,"domain_scores_codex":[0.9984883,0.00008545109,0.0002724307,0.0004112818,0.0002946059,0.0004479283],"domain_scores_gemma":[0.9994949,0.00005384764,0.00005688954,0.000283929,0.00000715697,0.0001032695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001097358,0.0001813384,0.9562955,0.00007775972,0.00002143164,0.00003036697,0.0001264345,0.0003597744,0.03946991,0.0003169825,0.002814045,0.0001967025],"study_design_scores_gemma":[0.0003936154,0.00005108658,0.9156054,0.00002616093,0.000007085464,0.000002900636,0.00003316025,0.0008762719,0.007021413,0.07565654,0.0001402463,0.0001861094],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975899,0.00001040958,0.00007345497,0.0006179042,0.0001821654,0.0002601365,0.00004643557,0.00003457725,0.001184947],"genre_scores_gemma":[0.9986104,0.00001521686,0.000370759,0.00002307481,0.00003465171,0.00004598885,0.0001124282,0.00001270461,0.0007747847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07533956,"threshold_uncertainty_score":0.9991292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02075838872610987,"score_gpt":0.2583200031434842,"score_spread":0.2375616144173743,"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."}}