Rare neural crest tumor in teleost species: olfactory neuroblastoma in a spotted pike-characin Boulengerella maculata
Bibliographic record
Abstract
One spotted pike-characin Boulengerella maculata, managed in a public display aquarium for 7 yr, developed a small unilateral pink growth associated with the right nare. The growth eventually extended through both nares after 5 mo. B. maculata is a species of piscivorous fish that relies on visual acuity when hunting prey. The rapidly-growing bilateral tumor would have impeded vision if left untreated. The fish was managed for over 10 mo using only surgical debulking, topical liquid nitrogen, and occasional nonsteroidal anti-inflammatory medications as needed to reduce tumor size and restore sight. Diagnosis proved challenging due to superimposed inflammation, neoplasm cellular inconsistencies, and a lack of proven immunohistochemical stains or other diagnostic stains. Using tumor location and appearance, histopathology, advanced imaging, electron microscopy, special staining, and immunohistochemistry, the ultimate diagnosis confirmed olfactory neuroblastoma, or esthesioneuroblastoma. Although long-term prognosis is poor, hunting strategy of the affected species may dictate quality of life, as appetite, body condition, and behavior remained largely unchanged in this animal until time of euthanasia.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".