Lungworm infections in harbour porpoises (Phocoena phocoena) in the German Wadden Sea between 2006 and 2018, and serodiagnostic tests
Bibliographic record
Abstract
) in German waters. The presented retrospective analysis including data from 259 harbour porpoises stranded between 2006 and 2018 on the German federal state of Schleswig-Holstein's North Sea coast showed that 118 (46%) of these stranded individuals harboured a lungworm infection. During this 13-year period, a significant difference in annual lungworm prevalence was only observed between the years 2006 and 2016. Lungworm coinfections of bronchi and pulmonary blood vessels were observed in 85.6% of positive cases. Mild infection levels were detected in 22.9% of infected animals and were most common in the age class of immature individuals (74.1%). Moderate and severe infections were present in 38.1% and 39.0% of the lungworm positive animals, respectively. Their distribution in immatures (51.1% and 54.3%) and adults (48.9% and 43.4%) did not show significant differences. In stranded animals, lungworm diagnosis can be easily obtained via necropsy, while reliable lungworm diagnosis in living porpoises requires invasive bronchoscopy or faecal examination, which is difficult to obtain in cetaceans. To overcome this issue, an enzyme-linked immunosorbent assay (ELISA) and immunoblot based on recombinant major sperm protein (MSP) of the cattle lungworm were evaluated as potential diagnostic tools in harbour porpoises. However, in contrast to hitherto other investigated host species, no reliable antibody response pattern was detectable in harbour porpoise serum/plasma or whole blood samples. Thus, MSP-based serological tests are considered unsuitable for lungworm diagnosis in harbour porpoises.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".