Bibliographic record
Abstract
Calcium plays an important role in many biological processes. At first, it might seem that the most important role of calcium in biology is a structural one, and indeed it may be argued that this is true. Hydroxyapatite, a co-crystal of calcium, phosphate, and hydroxide ions, forms the matrix of tooth enamel, the hardest substance in the human body. Calcium phosphate is also responsible for the rigidity of bone, and the deposition of this matrix in bone is a very tightly controlled biological process ( 1) . In fact, the vast majority of calcium (more than 99%) is immobilized in bones and teeth in humans. Poor diet or improper regulation of calcium deposition can lead to diseases such as childhood rickets or osteoporosis in older adults. Moreover, calcium is also important structurally in other organisms; for example, calcium carbonate is the major component of egg shells and also of the exoskeleton of animals such as mollusks and barnacles. Nutritionally, calcium is found in many foods, but of course the major source in most human diets is dairy products. In milk, a predominant class of proteins is the caseins, which function to solubulize calcium phosphate microgranules by surrounding them in a micellar structure ( 2) , providing an important mineral nutrient in liquid form. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.027 |
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".