In Search of Perfect Growth Media for Baker's Yeast Production: Mapping Patents
Bibliographic record
Abstract
Abstract: Baker's yeast is a key ingredient for bread and, on the long term, changes in its manufacturing process had a major impact on the baking industry. As shown by a review of 236 patents filed between 1900 and 2009, the development of suitable growth media for baker's yeast was critical to improve its acceptability by the baking industry mainly through reduced cost and improved appearance (pale color). Based on the abandon of patenting activity on artisan yeast production in dough, acceptable commercial baker's yeast appeared on the North American market around 1920, but probably 5 to 15 y earlier in Europe partly because German inventors were the most active to develop growth media for baker's yeast. During the same period, grain‐based media were replaced by diluted molasses that was cheaper. In the following 20 y, inventors put much energy on molasses clarification and miscellaneous sources of nitrogen to supplement it. Although molasses remains the basic raw material for baker's yeast manufacturing, alternatives are still sought for this application. In the early patent literature, cases were found where several inventors claimed intellectual property rights for the same invention described in patents filed in different countries and languages, which suggests that only thorough reading of patent specifications may distinguish inventorship from licenses and thus truly estimate patenting activity.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".