Genetic and morphometric categorization of<i>Taenia ovis</i>from Sheep in Iran
Bibliographic record
Abstract
Little is known about the genetic and morphological characters of Taenia ovis. The purpose of the present study was to characterize sheep isolates of T. ovis using rostellar hook morphometry as well as mitochondrial genes sequence analysis. Ninety sheep specimens of Cysticercus ovis were collected from 18 slaughterhouses in Iran. The mean ± s.d. for total length of large and small hooks were 174.1 ± 6.4 and 116.7 ± 5.4 µm, respectively. CO1 and 12S rRNA sequence analysis showed 11 and nine haplotypes, respectively. The level of pairwise nucleotide variations between individual haplotypes of CO1 and 12S rRNA genes were 0.3-1.1 and 0.2-1.0%, respectively. Level of nucleotide variation in CO1 and 12S rRNA between T. ovis haplotypes from present study and eight other Taenia species was found to be 11.3-17.8 and 5.3-16.3%, respectively. Phylogenetic analysis clustered all T. ovis isolates into a single clade comprised of the all CO1 and 12S rRNA haplotypes. CO1 nucleotide difference between T. ovis ovis and T. asiatica was 13.6% that is lesser than the corresponding difference between T. ovis ovis and T. ovis krabbei, warranting the designation of two separate species as T. ovis and T. krabbei. Interclass correlation coefficients showed that there was no significant association between rostellar hook length variation and the variability of the mitochondrial genes.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".