Non- Invasive Cone Beam Tomography (CBCT) to diagnose jaw bone Osteomyelitis in Sickle cell anaemia patients.
Bibliographic record
Abstract
Patients suffering from haemoglobinopathies most commonly show bone infection as a complication, of which Sickle cell anaemia (SCA) patients are the most susceptible to osteomyelitis. There are very few documented cases of jaw bone osteomyelitis in SCA patients. Keeping in mind the number of children diagnosed with SCA in India, this article reports how a commonly available and non-invasive radiographic method, dental CBCT, can be used to timely diagnose jaw bone osteomyelitis. Key Words : Sickle Cell Anemia ,Chronic Osteomyelitis , Jaw , Mandible , Case Report India , Sickle Cell Anemia complications , Radiograph , CBCT , Third molar pain , Onion skin appearance , Punched out lesions
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".