A multicontinuum approach for the problem of filtration of oily water systems across thin flat membranes: I. The framework
Bibliographic record
Abstract
A multicontinuum model is built to estimate the permeate flux of an oily water system across a thin flat membrane in cross filtration methodology is demonstrated. Several continua are constructed to represent droplet and pore‐size distribution of both the dispersed oil phase and the porous membrane, respectively. The possible permeation of the oil phase has been divided into three criteria. In the first criterion, oil droplets of a given size range may permeate through a given size range of the porous membrane, in the second criterion, oil droplets of another size range may be rejected through another pore size range, and in the third criterion, oil droplets may break apart leaving a tail inside the pore space, which will eventually permeate, and the rest will sweep off due to shear stress. These protocols identify the methodology of the proposed multicontinuum approach, which is introduced in this first part. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4604–4615, 2017
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".