Intelligent Quality Control of Starch-Rich Root and Tuber Products in the Cold Chain Logistics: Research Progress and Challenges
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
Starch-rich root and tuber products (RTs) are critical to maintaining food security worldwide. However, they are at risk of loss and waste because of postharvest physiological losses. Cold chain logistics (CCL) are essential for maintaining the quality of RTs and extending their shelf life during storage and transport. This review discusses the reasons for and phenomena of the quality deterioration of RTs in CCL and common nondestructive detection techniques for the quality of RTs. Environmental conditions are important factors influencing the postharvest quality of RTs. The application of Internet of Things (IoT) for real-time monitoring of environmental parameters of RTs in CCL is described in detail, especially sensor technology. Finally, methods targeting the quality management of RTs for all stages of CCL were presented.
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 | 0.006 | 0.002 |
| 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) | 0.000 | 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