Bibliographic record
Abstract
In the production of fermented foods, long-term preservation of the activity of microbial starters is a critical issue. The aim of this review was to determine key challenges in the production and use of active dry yeast over time and to compare statistics on letters patent for inventions and applied scientific articles as indicators of technological evolution. The review covers 280 original patent specifications and 212 applied scientific articles issued between 1796 and 2018, not including documents in basic science or without obvious application in fermented foods. The main subject matter was baking and the other entries applied to wine and, to a lesser extent, beer and spirits. Very popular in patents granted in the 19th century until about 1935 but ignored in the scientific literature, dehydrated yeast preparations often consisted of wet biomass concentrates mixed with large amounts of water-absorbing agents. Long-term survival of dehydrated yeast cells progressively improved with specific strains, growth conditions, and, to a lesser extent, drying conditions. Since the 1990s, both inventors and scientists have mainly targeted yeast cells protection during rehydration, a most critical factor. Proper review of the scientific literature would be incomplete unless it includes patents, a much ignored but relevant source of information.
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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".