{"id":"W3195924880","doi":"10.21105/joss.02276","title":"WDPM: the Wetland DEM Ponding Model","year":2021,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; Global Water Futures; Canada First Research Excellence Fund","keywords":"Ponding; Wetland; Environmental science; Hydrology (agriculture); Geography; Geology; Water resource management; Geotechnical engineering; Ecology; Biology; Drainage","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":[0.0004013628,0.0007963979,0.0004134434,0.0005811199,0.0004115965,0.0007886761,0.002230114,0.0006678129,0.03807114],"category_scores_gemma":[0.001922458,0.0005714848,0.0008479523,0.0006786993,0.0001984101,0.001045055,0.001021108,0.001007071,0.01177046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005113293,"about_ca_system_score_gemma":0.0009981575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01569239,"about_ca_topic_score_gemma":0.02886883,"domain_scores_codex":[0.9999083,0.00001443325,0.000007939607,0.00002776454,0.00002578868,0.00001569109],"domain_scores_gemma":[0.9997984,0.0000621265,0.00001333949,0.00004492613,0.00005883477,0.0000224092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004734307,0.0001613822,0.003595701,0.0004029562,0.0002251847,0.0003011959,0.0001968352,0.2734298,0.002019351,0.01599853,0.5352258,0.1679698],"study_design_scores_gemma":[0.0001989812,0.00002526271,0.0009245956,0.00004192571,0.00002748653,0.00009669254,0.00003263129,0.8981771,0.002368164,0.01295377,0.08511268,0.00004061619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.02269966,0.0004005916,0.5270801,0.000942157,0.0004660023,0.0006099078,0.1282214,0.2932357,0.02634448],"genre_scores_gemma":[0.2743421,0.0007702992,0.4828061,0.000670461,0.0001118432,0.001758585,0.1748738,0.03388407,0.03078279],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03807114,"threshold_uncertainty_score":0.1273607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02371119403593508,"score_gpt":0.2616894014135119,"score_spread":0.2379782073775768,"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."}}