Bibliographic record
Abstract
Tortuosity figures prominently in geochemical, hydrological, and geophysical calculations concerned with sediments, but it is a difficult parameter to measure. Past theoretical models for predicting the tortuosity from porosity data do not work with marine muds, and scientists and engineers have had to resort to entirely empirical models, without a mechanistic explanation and with unknown predictive power. We offer the first geometric model for the dependence of tortuosity on porosity in marine muds; the model is based on the tortuosity of separated layers of nonoverlapping disks. The fitted geometric constant in this model indicates that natural marine sediments act as if their fabric were made of disks with thickness:diameter ratios very close to 1:2, which indicates a blocklike fabric with respect to diffusion. The model was also applied to predict the tortuosity of a variety of sediments and soils not in the original database, and it provides a satisfactory prediction of the mean trend in these data. [KEYWORDS: tortuosity ; porosity ; mud ; modeling]
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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 | 0.002 |
| 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 | 0.001 |
| 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".