{"id":"W2608053858","doi":"10.1139/as-2015-0009","title":"Active layer slope disturbances affect seasonality and composition of dissolved nitrogen export from High Arctic headwater catchments","year":2017,"lang":"en","type":"article","venue":"Arctic Science","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Office of Polar Programs; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Government of Canada; ArcticNet","keywords":"Environmental science; Surface runoff; Seasonality; Nitrate; Disturbance (geology); Hydrology (agriculture); Arctic; Nitrogen; Drainage basin; Nutrient; Ecology; Chemistry; Geography; Biology; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003497094,0.0001298885,0.000196098,0.0000299289,0.0007033265,0.0001938156,0.0004313486,0.00003190226,0.001028156],"category_scores_gemma":[0.00005747794,0.0000974717,0.0000369275,0.00009477435,0.0009629579,0.0008203615,0.00007079873,0.00007989889,0.00003554221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001434528,"about_ca_system_score_gemma":0.00004350609,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04932711,"about_ca_topic_score_gemma":0.006853349,"domain_scores_codex":[0.998686,0.00003625254,0.0001508608,0.0004001904,0.00042336,0.0003033952],"domain_scores_gemma":[0.9990602,0.0001364342,0.0001764858,0.0003798379,0.00008160206,0.0001654325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006278263,0.00002136632,0.991559,0.00002055931,0.00001169645,0.000006022526,0.0006283672,0.000002774502,0.006121387,0.0000129408,0.00001039804,0.001542674],"study_design_scores_gemma":[0.0002472834,0.00007292982,0.9870155,0.00007048631,0.00002455806,0.000005776971,0.0001440822,0.0002983906,0.01003204,0.001934113,0.00002479545,0.0001299955],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974959,0.0001431273,0.000005630045,0.0004844823,0.0003313649,0.0001618252,0.0009435437,0.000008911599,0.0004252162],"genre_scores_gemma":[0.9991952,0.00006670566,0.0001376098,0.0001227874,0.00007624335,0.000002529913,0.0003808355,0.000002289088,0.00001580185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04247376,"threshold_uncertainty_score":0.999885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04452364123856313,"score_gpt":0.2853065968450961,"score_spread":0.240782955606533,"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."}}