Application of 1-Methylcyclopropene in Fresh-cut/Minimal Processing Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The application of 1-methylcyclopropene (1-MCP) in fresh-cut processing systems has been approached in three ways: 1) treatment of freshly harvested crop before longer-term storage after which the product is processed, 2) treatment of whole product just before processing, or 3) treatment of fresh-cut product immediately after processing. Results in the literature to date are quite variable in terms of whether 1-MCP treatment provides a benefit, no effect, or a negative effect on shelf life and quality retention of fresh-cut product. There are a number factors that impact the nature and extent of response to 1-MCP by fresh product and these include, but are not limited to, temperature of storage for fresh-cut product, condition of raw product, type of fruit or vegetable, cultivar, harvest maturity, duration of storage before cutting, and the 1-MCP treatment approach. A critical analysis, using existing published and unpublished data, provides a preliminary assessment of the impact of some of these factors. This analysis is intended to provide some insight into important considerations on the use of 1-MCP in fresh-cut processing systems and will guide researchers in considering experimental parameters for future work.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it