{"id":"W2810970914","doi":"10.1002/hyp.13213","title":"Stormwater capture and antecedent moisture characteristics of permeable pavements","year":2018,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Antecedent (behavioral psychology); Antecedent moisture; Stormwater; Environmental science; Water content; Hydrology (agriculture); Event (particle physics); Range (aeronautics); Surface runoff; Moisture; Soil science; Geotechnical engineering; Meteorology; Runoff curve number; Geology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0003878873,0.0002578852,0.0002792679,0.0006865766,0.0001405392,0.0004253588,0.0003079253,0.0002376672,0.0007134257],"category_scores_gemma":[0.001207967,0.0001511883,0.0002568355,0.0005633869,0.0002779387,0.0007521958,0.0002910424,0.000184078,0.00008885313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005185906,"about_ca_system_score_gemma":0.0001585629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003965199,"about_ca_topic_score_gemma":0.002859756,"domain_scores_codex":[0.9997776,0.00003018077,0.00001434928,0.00005430711,0.00006567439,0.00005791186],"domain_scores_gemma":[0.9994671,0.0002589941,0.0001355585,0.00005339332,0.00006039476,0.00002461029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002214432,0.0001259215,0.06972361,0.00006596037,0.0001009804,0.0001723559,0.00009846511,0.8140066,0.09489876,0.0009490914,0.0001154375,0.0195213],"study_design_scores_gemma":[0.00000751103,0.0001551713,0.08418152,0.000005256822,0.00002876297,0.00007144436,0.00008709604,0.8582323,0.05641292,0.000501833,0.0002850909,0.00003107054],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864658,0.00003664271,0.01286318,0.000005863119,0.00000179759,0.000007339698,0.0001156661,0.00005883673,0.0004450249],"genre_scores_gemma":[0.9996316,0.000009868304,0.0002703439,5.033365e-7,3.381337e-7,0.00000177214,0.00003514991,0.000002172497,0.0000481518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003965199,"threshold_uncertainty_score":0.007884264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280983490726143,"score_gpt":0.2140933014195522,"score_spread":0.2012834665122908,"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."}}