An Assessment of Alternative Cap Covers for the King Road Landfill
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is difficult to design Evapotranspiration (ET) covers that satisfy performance requirements for solid waste landfills in humid regions that are also economical because of the excess precipitation relative to evapotranspiration. The Ohio EPA is allowing a remedial option wherein native plants can be included in the vegetative configuration for creating an ET cover for the former King Road Landfill, located in Lucas County, Ohio, to restore more than 100 acres of local Oak Openings ecosystem. The objective of this research is to utilize numerical models to predict the effectiveness of an ET cover that incorporates native plants and soil that is derived from waste materials. The alternative cover material that is being considered is NU-Soil, a locally mixed soil of dredged material and biosolids stabilized with waste lime from a water treatment plant. Trial 365-day simulations of six lysimeters were conducted with Virginia wild rye as the vegetative cover using HYDRUS 2D. Several 365-day simulations were conducted on a section of the landfill cover. The neural network option in HYDRUS 2D based on the textural percentages and the bulk density of the NU-Soil was utilized to predict soil retention functions as well as the hydraulic conductivity function. The results of the lysimeter simulation gave cumulative water at the bottom of the lysimeter of 56 cm which does not meet the regulatory requirement of less than 32 cm of flux through an ET cover but it is possible that the cover will satisfy this requirement if evaporation is included in the analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it