Laboratory Column Test for Predicting Changes in Flow with Changes in Various Biofilter Mixtures
Bibliographic record
Abstract
The performance of biofiltration and other infiltration systems in urban areas is affected by factors such as media particle size distributions and uniformity, and the degree of compaction during construction. This paper describes a series of controlled laboratory column tests conducted using various biofilter media to measure changes in flow with changes in the mixture characteristics, focusing on media density associated with compaction, particle size distribution (and uniformity), and amount of organic material (due to added peat). The results of the performance measurements of these mixtures were also verified using column tests (for different compaction conditions) of surface and subsurface soil samples obtained from Tuscaloosa, Alabama along with biofilter media obtained from Kansas City, North Carolina, and Wisconsin. The results of the full factorial analyses indicate that texture and uniformity of the media mixture have the greatest effect on the measured final infiltration rates of the media. The organic matter in the biofilter media does not have a significant effect by itself on the infiltration rate compared to the other factors (texture, uniformity and compaction). However the organic matter serves as a reservoir of nutrients and water in the biofilter media and increases water infiltration into the media.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".