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Mapping Early Patents on Baker's Yeast Manufacture

2010· article· en· W2056727825 on OpenAlexaff
Pierre Gélinas

Bibliographic record

VenueComprehensive Reviews in Food Science and Food Safety · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsAgriculture and Agri-Food Canada
FundersOffice of Science
KeywordsYeastAutomationTasteFood scienceBiotechnologyBusinessBiologyEngineeringBiochemistryMechanical engineering

Abstract

fetched live from OpenAlex

In the 19th century, bread had a pronounced acidic taste and a nonuniform appearance, as shown by a review of 178 early patents families on baker's yeast manufacture. This was largely due to the unpredictable nature of baker's yeast, which was generally grown under empiric conditions in nonsterile dough or liquid prepared with saccharified cereals. Inventors were mainly interested in techniques to increase yields of pressed yeast through media formulation, infection control, and automation of biomass separation and packaging. Still in its infancy, baker's yeast technology was slow to develop and apply new ideas due to lack of awareness on information published in patents and the scientific literature. This review also gives background information on early patents.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.007

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.

Opus teacher head0.064
GPT teacher head0.269
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreReview

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".

Quick stats

Citations25
Published2010
Admission routes1
Has abstractyes

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