Use of a Pressuremeter To Measure the Kinetics of Carbon Dioxide Evolution in Chemically Leavened Wheat Flour Dough
Bibliographic record
Abstract
Among a number of impediments to a wider use of chemical leavening agents in bakery applications is the lack of standardized instrumentation capable of providing information on the rates of CO2 production from chemical leaveners in a format that is meaningful to both the technologist (i.e., the dough rate of reaction or DRR) and the researcher (e.g., in terms of fundamental unitskmol CO2 per kg of dough per s). This paper presents an original methodology to carry out the DRR test using a commercial pressuremeter, the Gassmart apparatus, and to model the kinetics of CO2 evolution of chemically leavened dough. Lean formula doughs were leavened at 27 and 39 degrees C with four chemical leavening systems containing sodium bicarbonate and one of four leavening acids, sodium acid pyrophosphate 40 (SAPP), adipic acid (ADA), potassium acid tartrate (KAT), and glucono-delta-lactone (GDL). Chemical kinetics theory was used to gain an insight into the reaction mechanisms responsible for the evolution of carbon dioxide from the leaveners. A first-order reaction kinetics model was found to be suitable for describing the neutralizing properties of GDL and ADA leavening systems, whereas a first-order reaction kinetics model for irreversible parallel reactions better described the leavening properties of the acidic salts KAT and SAPP.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".