Underground storage tanks (UST): A closer investigation statistical implications to changing the shape of a UST
Bibliographic record
Abstract
Gasoline service stations that use underground storage tanks (UST) assume that the manufactured tank is an ideal cylindrical shape. This cross-sectional shape plays a crucial role in determining a functional form for the volume of liquid that remains inside the tank. In industry, these formulas are used to compute strapping charts. But realistically, the manufacture, assembly, and installation of a tank may have deviation from the actual tank design (for which strapping charts had been developed). A theoretical volume function (based on tank dimensions) is used alongside of statistical methodology to reconcile volume differences in gasoline dispensed at the pump meters versus that displaced inside the tank. Statistical inventory reconciliation of this nature falls within the family of leak detection methods approved by the EPA (Environmental Protection Agency) and the California Water Resources Board. This methodology can also be used to assess deformation of the cross-sectional shape of the tank. We consider a deformation to an ellipse. Through simulation, we estimate the tank dimensions based on a nonlinear model with normal errors. The use of normal errors naturally facilitates a likelihood ratio test. Through this exploration, an approximation function is developed to help improve the power of the likelihood ratio test.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".