{"id":"W4385761072","doi":"10.2166/wcc.2023.429","title":"The new ‘surface storage’ concept versus the old ‘sponge effect’ concept: application to the analysis of the spatio-temporal variability of the annual daily maximum flow characteristics in southern Quebec (Canada)","year":2023,"lang":"en","type":"article","venue":"Journal of Water and Climate Change","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wetland; Hydrology (agriculture); Snowmelt; Surface runoff; Environmental science; Shore; Water storage; Duration (music); Surface water; Period (music); Magnitude (astronomy); Water level; STREAMS; Spatial variability; Physical geography; Geography; Ecology; Geology; Oceanography; Cartography","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":[0.0009421266,0.0001585106,0.0002080013,0.00102491,0.0003267942,0.0008340271,0.000306911,0.0001582211,0.001222895],"category_scores_gemma":[0.001674871,0.00005266879,0.0003305527,0.001613458,0.0007142315,0.000340406,0.0003406251,0.000189619,0.00005734389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003419547,"about_ca_system_score_gemma":0.002606147,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7175534,"about_ca_topic_score_gemma":0.7308461,"domain_scores_codex":[0.999762,0.00006945751,0.00001229795,0.0000496443,0.00006309732,0.00004352094],"domain_scores_gemma":[0.9988895,0.0005203605,0.0001684437,0.00008503853,0.0002434661,0.00009315467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009291508,0.00001971105,0.9642459,0.00003145575,0.0001021673,0.0001571711,0.00042538,0.01223205,0.001281201,0.001153749,0.0006794925,0.01957873],"study_design_scores_gemma":[0.000003788996,0.00004167846,0.9709536,0.00001048992,0.00001817213,0.00004380321,0.0006144769,0.02680388,0.0001647675,0.0002400574,0.001094242,0.00001106963],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950001,0.0001276194,0.00278063,0.0001341579,0.000006161617,0.00001249552,0.0005781774,0.00002342493,0.001337213],"genre_scores_gemma":[0.9990951,0.00002482482,0.0005513725,0.000007497651,0.000003438799,0.000003306328,0.0001240522,0.000002495557,0.0001879133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2824466,"threshold_uncertainty_score":0.5682199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00983282630138966,"score_gpt":0.2200086403753827,"score_spread":0.2101758140739931,"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."}}