Minerals In Food: Crystal Structures of Ikaite and Struvite From Bacterial Smears On Washed-Rind Cheese
Bibliographic record
Abstract
Abstract Food contains inorganic elements and compounds that are important for human nutrition and human health. Although these substances have been investigated and characterized in many foods for their nutritive value, little is known about the crystal phases that form in foods. In this study, we investigated crystals that form in the bacterial smears on the surface of washed-rind cheese. Washed-rind cheeses have been consumed for centuries, but the crystals that often contribute detectable grittiness to the surface of these cheeses have never been identified. The crystals were characterized with petrographic microscopy and identified with single crystal X-ray diffractometry as ikaite (CaCO 3 ·6H 2 O), a rare metastable phase that has only been observed in freezing marine and lacustrine environments, and struvite (NH 4 MgPO 4 ·6H 2 O), a mineral that is often associated with bacterial activity. These crystals are important to cheesemakers because they affect cheese texture and sensory characteristics. The potential importance of the bacterial smear in the nucleation of these phases is discussed, and the possibility of using cheese as a model system to investigate geological biomineralization phenomena is explored.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".