Phylogenetic analysis and taxonomic distinction of six genera of pathogenic scuticociliates (Protozoa, Ciliophora) inferred from small-subunit rRNA gene sequences
Bibliographic record
Abstract
Pathogenic scuticociliates, which are common in the haemolymph or tissues of maricultured animals and often cause serious diseases, are a species-rich assemblage with mostly unresolved systematic relationships, especially in some less-studied groups. In the present study, we sequenced the small-subunit rRNA gene of six species of scuticociliates, Uronemella parafilificum, Metanophrys sinensis, Parauronema longum, Cohnilembus verminus, Porpostoma notata and Ancistrum crassum, the last two of which have not been studied previously using molecular analyses. Phylogenetic trees were constructed using Bayesian inference, maximum-likelihood and maximum-parsimony methods to assess the inter- and intra-generic relationships of scuticociliates. Results revealed the following: 1) Porpostoma did not cluster with the Philasteridae, Cohnilembidae or any other family of the order Philasterida; 2) sequences of Uronemella parafilificum and Uronemella filificum showed a difference of 1.02% (15 nt sites), revealing a close relationship between them; 3) the approximately unbiased test rejected monophyly of both Metanophrys and Parauronema, indicating that the terminal position of the anterior end of the paroral membrane and the structure of membranelle 1 are unreliable characters for distinction of genera in this group of scuticociliates; 4) Ancistrum crassum grouped with Boveria subcylindrica, showing a close phylogenetic relationship between the orders Thigmotrichida and Pleuronematida; and 5) Parauronema longum, Cyclidium plouneouri and Cyclidium porcatum should be removed from their currently assigned genera.
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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 | 0.001 | 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".