A multicontinuum approach for the problem of filtration of oily‐water systems across thin flat membranes: II. Validation and examples
Bibliographic record
Abstract
In this second part, a validation exercise is conducted to investigate the accuracy of the multicontinuum approach in estimating the permeation capacity of membranes used for the filtration of oily‐water systems. Comparisons with the experimental works found in the literature reveals that the multicontinuum approach is quite accurate and show excellent match. Although the comparisons with the experimental data have been with respect to macroscopic integral variables, like the rejection capacity of membranes, the multicontinuum approach provides myriad information about the permeation process that have neither been presented nor even measured. Such detailed information has been highlighted in two examples. Details about which of the oil continua is going to be rejected or permeated through which porous membrane continuum are obtained. Furthermore, the flux of each oil continuum through every porous membrane continua is likewise obtained. These informations are then lumped to calculate the rejection capacity of membranes. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1095–1105, 2018
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".