Validating the identity of Paramoeba invadens, the causative agent of recurrent mass mortality of sea urchins in Nova Scotia, Canada
Bibliographic record
Abstract
Green sea urchins Strongylocentrotus droebachiensis along the coast of Nova Scotia, Canada, suffer mass mortalities from infection by the pathogenic amoeba Paramoeba invadens Jones, 1985. It has been speculated that P. invadens could be a form of Neoparamoeba pemaquidensis, a species associated with disease in S. droebachiensis and lobsters in the northeast USA. During a disease outbreak in fall 2011, we isolated amoebae from moribund urchins collected from 4 locations along ~200 km of coastline. In laboratory infection trials, we found that timing and rate of morbidity corresponded to that of similar experiments conducted in the early 1980s, when P. invadens was first identified. All isolates had a similar size and morphology to the original description, including an absence of microscales. Sequences of nuclear SSU rDNA show that disease was caused by one 'species' of amoeba across the range sampled. Phylogenetic analyses prove that P. invadens is not conspecific with N. pemaquidensis, but is a distinct species most closely related to N. branchiphila, a suspected pathogen of sea urchins Diadema aff. antillarum in the Canary Islands, Spain. Morphology and closest phylogenetic affinities suggest that P. invadens would be assignable to the genus Neoparamoeba; however, nuclear SSU rDNA trees show that Neoparamoeba and Paramoeba are phylogenetically inseparable. Therefore, we treat Neoparamoeba as a junior synonym of Paramoeba, with P. invadens retaining that name, and N. pemaquidensis and N. aestuarina reverting to their original names (P. pemaquidensis and P. aestuarina), and with new combinations for N. branchiphila Dykova et al., 2005, and N. perurans Young et al., 2007, namely P. branchiphila comb. nov. and P. perurans comb. nov.
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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 | 0.000 | 0.000 |
| 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".