Bibliographic record
Abstract
An approximately 1-year-old male neutered Labrador retriever was referred for evaluation of a previously diagnosed congenital cleft palate. Prior to referral, the primary care veterinarian had performed two unsuccessful attempts at repair. A complete physical examination at the time of presentation revealed a defect in the rostral secondary and mid-??secondary hard palate, mild generalized calculus, severe halitosis, class I malocclusion with linguoversion of both mandibular canines, mild discharge from the left eye and a periorbital swelling ventral to the left eye. Select preoperative diagnostics included point-??of-??care bloodwork, computed tomography of the skull and full-??mouth radiographs; intraoperative aerobic, naerobic, and fungal cultures were obtained from the nasal cavity via the palatal cleft. Based on the history, physical examination, and diagnostics performed, a congenital, non-??syndromic, complete secondary cleft palate was diagnosed. A combination two-??flap and modified von Langenbeck palatoplasty was performed to reconstruct the secondary palatal defect; the soft palate was reconstructed using a 3-??layer direct apposition technique. Recovery from surgery and anesthesia was uneventful and the patient was discharged the following day. Approximately 5 weeks post-??operatively, a recheck examination under general anesthesia revealed three 1-??2mm palatal defects at the hard-??soft palate junction; all preoperative clinical signs had resolved and the pinpoint palatal defects did not appear to be causing clinical signs. The palatal defects were corrected by incising and apposing the palatal mucosa. The class I malocclusion was corrected by partial coronal pulpectomy of the mandibular canines. Surgical outcome was considered excellent.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".