Advancements in Characterizing Tenacibaculum Infections in Canada
Bibliographic record
Abstract
Tenacibaculum is a genus of gram negative, marine, filamentous bacteria, associated with the presence of disease (tenacibaculosis) at aquaculture sites worldwide; however, infections induced by this genus are poorly characterized. Documents regarding the genus Tenacibaculum and close relatives were compiled for a literature review, concentrating on ecology, identification, and impacts of potentially pathogenic species, with a focus on Atlantic salmon in Canada. Tenacibaculum species likely have a cosmopolitan distribution, but local distributions around aquaculture sites are unknown. Eight species of Tenacibaculum are currently believed to be related to numerous mortality events of fishes and few mortality events in bivalves. The clinical signs in fishes often include epidermal ulcers, atypical behaviors, and mortality. Clinical signs in bivalves often include gross ulcers and discoloration of tissues. The observed disease may differ based on the host, isolate, transmission route, and local environmental conditions. Species-specific identification techniques are limited; high sequence similarities using conventional genes (16S rDNA) indicate that new genes should be investigated. Annotating full genomes, next-generation sequencing, multilocus sequence analysis/typing (MLSA/MLST), matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF), and fatty acid methylesters (FAME) profiles could be further explored for identification purposes. However, each aforementioned technique has disadvantages. Since tenacibaculosis has been observed world-wide in fishes and other eukaryotes, and the disease has substantial economic impacts, continued research is needed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".