Persistent fontanelles in Chihuahuas. Part I. Distribution and clinical relevance
Bibliographic record
Abstract
BACKGROUND: The Chihuahua dog breed is known for frequent occurrence of a bregmatic fontanelle on the dorsal skull. A common conception is that this skull defect is a clinically irrelevant finding. No studies, however, describe its prevalence or whether it is accompanied by other persistent fontanelles (PFs). Although Chihuahuas are predisposed to Chiari-like malformation (CM) and syringomyelia (SM), it is unknown whether PFs occur more commonly in dogs with clinical signs that are caused by CM or SM. HYPOTHESIS/OBJECTIVES: To describe the number and location of PFs at cranial sutures (CSs) and to compare the occurrence of these PFs in dogs with and without CM/SM-related clinical signs. We hypothesized that PFs also occur commonly at lateral and caudal cranial surfaces, affect a higher number of CSs, and are larger in dogs with CM/SM-related clinical signs. ANIMALS: Fifty client-owned Chihuahuas with or without CM/SM-related clinical signs. RESULTS: Of the 50 dogs evaluated, 46 (92%) had either 1 or several PFs. The mean ± SD number of PFs was 2.8 ± 3.0 (range, 0-13). A total of 138 PFs occupied 118 CSs with 57 (48%) located dorsally, 44 (37%) caudally, and 17 (14%) laterally. The number of CSs affected by PFs was significantly higher (P ≤ .001) and total PF area was significantly larger (P = .003) in dogs with CM/SM-related clinical signs. CONCLUSIONS AND CLINICAL IMPORTANCE: Persistent fontanelles are very common in this group of Chihuahuas and appear at dorsal, lateral, and caudal cranial surfaces. They are more numerous and larger in Chihuahuas with CM/SM-related clinical signs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".