Bibliographic record
Abstract
The chapter explores the prevalent neurological diseases affecting both wild and farmed deer, focusing on enzootic ataxia, tetanus, meningoencephalitis (including listeriosis), Louping ill, polioencephalomalacia (PE), cerebrospinal nematodiasis, and botulism. The chapter offers comprehensive insights into the clinical signs, pathology, diagnosis, treatment, and contributing factors of these diseases, such as copper deficiency and high levels of ingested molybdenum in the case of enzootic ataxia. Significant works, including Smits and Wobeser's (1990) case study of polioencephalomalacia (PE) in a captive fallow deer, Suttle's (2022) chapter on copper in mineral nutrition of livestock, Tyler et al. ‘s (1980) experimental studies on Parelaphostrongylus tenuis infection in mule deer, and Wilson et al. ‘s (1979) research on enzootic ataxia in red deer, are referenced. The chapter also references Wobeser and Runge's (1979) study on PEM in white-tailed deer in Saskatchewan, offering insights into the prevalence of this disorder in North American deer populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".