Fluorosis detected by trephine biopsy
Bibliographic record
Abstract
A 45-year-old man presented with low back pain and difficulty ambulating. A magnetic resonance imaging scan of the brain and lumbosacral spine demonstrated homogeneous replacement of normal marrow and routine chest radiograph revealed diffuse osteosclerosis (top left). He was referred to rule out an infiltrative marrow process. Iliac crest biopsy demonstrated normal trilineage haematopoeisis with markedly sclerotic cortical bone and thickened bony trabeculae (top right). There was no evidence of metastatic cancer or granulomatous disease. Bone mineral density Z-scores of lumbar spine and femoral neck were +10·8 and +10·9 respectively, confirming osteosclerosis. On further history, the patient admitted to ingesting five tubes of toothpaste per week for 30 years. Serum fluoride level was 44·2 μmol/l (reference 1·0–4·6 μmol/l), supporting a diagnosis of skeletal fluorosis. Skeletal fluorosis is caused by excessive fluoride ingestion. Although under-recognized in developed nations, it affects millions worldwide due to contaminated well water. Moderate exposure leads to dental effects such as staining and pitting of teeth and damage to enamel (bottom). Long-term ingestion may lead to skeletal abnormalities including debilitating arthralgias and impairment of cervical and lumbar mobility. Symptoms have been reported to resolve slowly after removal of fluoride.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".