{"id":"W6892990897","doi":"10.5281/zenodo.13127717","title":"Cycles in hydrologic intensification and de-intensification create instabilities in spring nitrate-N export C-Q behavior in northern temperate forests","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Canadian Forest Service; University of Toronto","funders":"","keywords":"Snow; Evapotranspiration; Precipitation; Spring (device); Hydrology (agriculture); Wetland; Temperate rainforest; Hydrological modelling; Snowmelt","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":[0.0003121223,0.00008375881,0.00009806807,0.0002689068,0.0002698216,0.0003076143,0.0001865085,0.00007425001,0.004185152],"category_scores_gemma":[0.0006346627,0.00007228191,0.0003100132,0.0004967639,0.00008249079,0.0002027013,0.0001825263,0.00008593122,0.0003584505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007739383,"about_ca_system_score_gemma":0.0006809459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06757087,"about_ca_topic_score_gemma":0.1774527,"domain_scores_codex":[0.999912,0.00001139678,0.000008552255,0.00002608694,0.00002829004,0.00001370388],"domain_scores_gemma":[0.9996371,0.0001203836,0.00007619341,0.00002680616,0.0001061066,0.00003351796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002704093,0.0000693179,0.9515901,0.0001199339,0.00007905028,0.0001593472,0.0006462399,0.003025071,0.006682223,0.0004470283,0.01143862,0.02547264],"study_design_scores_gemma":[0.00001240096,0.00002049299,0.9922876,0.00001186039,0.0000147388,0.00002028056,0.0002443907,0.001357967,0.001170394,0.0001159029,0.004740022,0.000003895967],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9609399,0.0000594725,0.0005383635,0.0001385198,0.000006883758,0.00005251659,0.02816791,0.00007451261,0.01002185],"genre_scores_gemma":[0.9683346,0.0001622634,0.001837815,0.00005777944,0.000008908723,0.00009320981,0.02480481,0.00002741976,0.004673206],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.06757087,"threshold_uncertainty_score":0.1343551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04274207274029625,"score_gpt":0.2695347381090989,"score_spread":0.2267926653688027,"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."}}