Identifying the core microbiome of the sea star<i>Pisaster ochraceus</i>in the context of sea star wasting disease
Bibliographic record
Abstract
Sea stars are keystone species and their mass die-offs due to sea star wasting disease (SSWD) impact marine communities and have fueled recent interest in the microbiome of sea stars. We assessed the host specificity of the microbiome associated with three body regions of the sea star Pisaster ochraceus using 16S rRNA gene amplicon surveys of the bacterial communities living on and in Pisaster, their environment, and sympatric marine hosts across three populations in British Columbia, Canada. Overall, the bacterial communities on Pisaster are distinct from their environment and differ by both body region and geography. We identified core bacteria specifically associated with Pisaster across populations and nearly absent in other hosts and the environment. We then investigated the distribution of these core bacteria on SSWD-affected Pisaster from one BC site and by reanalyzing a study of SSWD on Pisaster from California. We find no differences in the distribution of core bacteria in early disease at either site and two core taxa differ in relative abundance in advanced disease in California. Using phylogenetic analyses, we find that most core bacteria have close relatives on other sea stars and marine animals, suggesting these clades have evolutionary adaptions to an animal-associated lifestyle.
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 | 0.000 |
| 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) | 0.001 | 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".