Bibliographic record
Abstract
Poly(methacrylic acid) (PMAA) grafted porous PE membranes (PE-g-PMAA) were studied. It was found that (1) a wide range of graft yields can be achieved by varying irradiation time (20–240 min) and monomer concentration (0.22M–0.66M), (2) the grafted membrane exhibits reversible permeability response, (3) the membrane shows a maximum permeability response at an intermediate permeant molecular weight due to size exclusion effect, and (4) depending on the graft yield, two types of permeability response can be obtained. These observations are consistent with our earlier study on poly(N-isopropylacrylamide) (PNIPAAm)–grafted porous polyethylene membranes. In addition, it was observed that the solvent used during grafting may influence the graft location—presumably due to variations in pore wetting. Specifically, compared to water solvent, methanol can increase grafting inside membrane pores, an observation inferred from membrane swelling, thickness measurement, and SEM characterization. Moreover, preferential grafting inside the membrane pores, as affected by increasing methanol content in the grafting solvent, results in lower membrane permeability and a greater pore graft-controlled type of permeability response. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 76: 778–786, 2000
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".