Bibliographic record
Abstract
Prior research by Pitt (1987) examined runoff losses from paved and roofed surfaces in urban areas and showed significant losses at these surfaces during the small and moderate sized events of most interest for water quality evaluations.However, Pitt and Durrans (1995) also examined runoff and pavement seepage on highway pavements and found that very little surface runoff entered typical highway pavement.During earlier research, it was also found that disturbed urban soils do not behave as indicated by stormwater models.Early unpubli'ihed double-ring infiltration tests conducted by the Wisconsin Department of Natural Resources (DNR) in Oconomowoc, Wisconsin, (shown in Table indicated highly variable infiltration rates for soils that were generally sandy {NRCS A and B hydrologic group soils) and dry.The median initial rate was about 75 (3 in/h), but ranged from 0 to 600 mm/h (0 to 25 in/h).The final rates aLso had a median value of about 75 mm/h (3 in/h) after at least two hours of testing, but ranged from 0 to 400 mm/h (0 to 15 in/h).Many infiltration rates actually increased with time during these tests.In about one third of the cases, the observed infiltration rates remained very dose to zero, even for these sandy soils.Areas that experienced substantial disturbances or traffic (such as school playing fieids), and siltation (such as in some grass swales) had the lowest infiltration rates.H was hoped that more detailed testing could explain some of the large variations observed.In an attempt to explain the variations observed in early infiltration tests in disturbed urban soils, tests were conducted in the Birmingham, Alabama, area by the authors, assisted by UAB hydrology students.About 150 individual double-ring ----------------• --•~~-•-----Pitt, RE and l Lantrip.2000."Infiltration Through Disturbed Urban Soils."
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".