Bibliographic record
Abstract
Starch is a water-insoluble polyglucan synthesized inside the plastids of plant tissues to provide a store of carbohydrate. Starch harvested from plant storage organs has probably represented the major source of calories for the human diet since before the dawn of civilization. Following the advent of agriculture and the building of complex societies, humans have maintained their dependence on high-yielding domesticated starch-forming crops such as cereals to meet food demands, livestock production, and many non-food applications. The top three crops in terms of acreage are cereals, grown primarily for the harvestable storage starch in the endosperm, although many starchy tuberous crops also provide an important source of calories for various communities around the world. Despite conservation in the core structure of the starch granule, starches from different botanical sources show a high degree of variability, which is exploited in many food and non-food applications. Understanding the factors underpinning starch production and its final structure are of critical importance in guiding future crop improvement endeavours. This special issue contains reviews on these topics and is intended to be a useful resource for researchers involved in improvement of starch-storing crops.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".