Hydraulic Head Hydrographs from Depth-Discrete High Resolution Multilevel Systems for Estimating Loading Efficiency and Specific Storage in a Silurian Dolostone Aquifer in Guelph, Ontaio
Bibliographic record
Abstract
This study involves the application of the poroelastic theory of loading efficiency to a dolostone aquifer at a study site within the City of Guelph. At this 10 hectare site the Silurian ( 443 - 419 Ma) dolostone aquifer is 100m thick, covered by a thin layer of anthropogenic fill and underlain by an extensive deposit of low permeability shale. This study site is instrumented with five multilevel systems (MLS) with 51 total pressure transducers, and relies upon collected pore water time series datasets to determine depth-discrete loading efficiency profiles. The loading efficiency profiles are used to assess degree of confinement, and estimates of undrained uniaxial specific storage which are assessed for reasonableness against literature values and a traditional pumping test analysis previously conducted and monitored with the same infrastructure. The loading efficiency approach incorporated the heterogeneity of fractured dolostone rock aquifers in determining aquifer hydraulic properties.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".