Structure and gas transmission characteristics of microperforations in plastic films
Bibliographic record
Abstract
Abstract Bright field transmitted light microscopy (BFTLM), differential interference contrast light microscopy (DICLM), conventional scanning electron microscopy (SEM) and low‐vacuum scanning electron microscopy (LV‐SEM) were used to observe microperforations in plastic film used for modified atmosphere packaging. Characteristics of the microperforations, including size, shape and obstructions are indicators of consistency and reproducibility of the process used to produce the microperforations. In addition, the microperforations appeared differently on the upper and lower surfaces of the plastic films, including a local thickening at the site of the microperforation and size of the opening. Microperforations in the range of 30 to 100 µm in diameter exhibited a linear increase of both O2 and CO2 transmission rates with hole area, for diffusion under calm conditions. Further testing indicated that microperforations larger than 55 µm in diameter can lose their diffusion constant if convection is present. Holes with a diameter less than 55 µm should therefore be used to achieve the required oxygen transmission rates (OTR). Copyright © 2007 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.
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 | 0.000 |
| 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 | 0.000 |
| 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".