Anthropogenic introduction of the etiological agent of withering syndrome into northern California abalone populations via conservation efforts
Bibliographic record
Abstract
Populations of abalone have precipitously declined in California over the past several decades, largely as a result of fishing pressure and disease. Because of these declines, farmed seed abalone have been planted in an attempt to research and restore dwindling populations. Withering syndrome is a chronic disease responsible for mass mortalities of wild black abalone, Haliotis cracherodii, in southern and central California and is caused by the bacterium "Candidatus Xenohaliotis californiensis". This bacterium has been observed in wild populations of black and red (Haliotis rufescens) abalone south of Carmel and in farmed red abalone throughout the state. In an effort to elucidate the distribution and source of the bacterium in northern California, the presence or absence of the disease and bacterium was verified at 15 locations north of Carmel. This research revealed that both the bacterium and withering syndrome are present in abalone populations south of San Francisco. In addition, the bacterium (but not withering syndrome) is present at two locations in northern California, both associated with outplants of hatchery-reared abalone, suggesting a link between restoration efforts and the present distribution of this pathogen. These data highlight the need for careful assessment of animal health before restocking depleted populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".