{"id":"W2790588890","doi":"10.3390/w10020133","title":"Determining Surface Infiltration Rate of Permeable Pavements with Digital Imaging","year":2018,"lang":"en","type":"article","venue":"Water","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"University of Victoria","keywords":"Natural rubber; Materials science; Asphalt; Porosity; Composite material; Geotechnical engineering; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00009984877,0.00008068681,0.00006327993,0.00001784773,0.00009659864,0.00005697977,0.000106449,0.00001090017,0.001047457],"category_scores_gemma":[0.000002268556,0.00005375234,0.00001493529,0.00006167207,0.0001912407,0.0007487208,0.0001330255,0.00002662739,0.000813859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004759993,"about_ca_system_score_gemma":0.000001901646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009902564,"about_ca_topic_score_gemma":0.00003682621,"domain_scores_codex":[0.9993513,0.00001297296,0.0001211383,0.0001687066,0.0001259777,0.0002198556],"domain_scores_gemma":[0.9997502,0.000004381416,0.00003513193,0.0001701665,0.00000910978,0.000030998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001352304,0.00003978385,0.8716301,0.000005618018,0.00001453139,0.000004328276,0.001542775,0.000766694,0.1235679,0.00001050173,0.001803545,0.0006006288],"study_design_scores_gemma":[0.001465239,0.0004617114,0.324206,0.00006172535,0.00007108256,0.00001362448,0.0005023246,0.01879241,0.5988629,0.0006180143,0.05423467,0.0007103239],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769704,6.915251e-7,0.002153441,0.00008357345,0.00004872342,0.0001043681,0.0000028986,0.00002846792,0.02060743],"genre_scores_gemma":[0.9952388,2.279671e-7,0.0007212605,0.00008993066,0.00001798987,0.000003369769,0.0000124567,0.00001036419,0.003905561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5474242,"threshold_uncertainty_score":0.9999641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006655635436707031,"score_gpt":0.1870517834108636,"score_spread":0.1803961479741565,"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."}}