NBEP-16-190: Stormwater Outfall Assessment for the East and West Monponsett Ponds
Bibliographic record
Abstract
The objective of this project is to identify, map, and prioritize the stormwater outfalls, scuppers, and other point sources discharging to the East and West Monponsett Ponds (Halifax, MA). The three highest ranked priority outfalls will have preliminary designs developed for them. There are estimated to be 20 outfalls. Emphasis for designs will be placed on the use of Best Management Practices (BMPs) and low impact development as recommended by previous EPA modelling completed for the contributing watershed. Methodology used to map the outfalls will be to field locate from both land and water. Several outfalls are visible and are known by Town staff, but additional outfalls, scuppers, and point sources are expected to exist based on existing drainage infrastructure within the watershed. Once located, upstream drainage structures will be opened and investigated to delineate the contributing drainage area. Using aerial photography, GIS information, and LiDAR information, the contributing impervious area will be developed. Other criteria will be considered asdescribed in the grant application. The output is a prioritization and preliminary design for three outfalls discharging to the ponds. This will be valuable information that the Town will need for future grant funded efforts toimplement BMPs within the watershed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".