The Effect of DB1976 on the Fibrotic Response in Three-spined Stickleback (Gasterosteus aculeatus)
Bibliographic record
Abstract
The study of fibrosis in stickleback has been a growing field in which there have been a few studies conducted. This study examines two experiments involving the inhibition of fibrosis in stickleback. The first experiment used fish from the Kenai River Flats (KRF) in Alaska. The second experiment used fish from Roselle Lake in British Columbia, Canada. To determine the impact the drug had on fibrosis, sticklebacks from the KRF population were treated with DB1976 as well as alum, a pro‐inflammatory vaccine adjuvant that causes fibrosis (Kool et. al 2012). When each DB1976 + alum treatment group was compared with the alum treatment group, a significant reduction in fibrosis was found. With the Roselle Lake population, alum as well as proteins from S. solidus, a parasite found in Roselle Lake, were used to initiate fibrosis. No significant reduction in fibrosis was observed in either the DB1976 + worm protein group or the DB1976 + alum group. These results demonstrate a difference in response to treatment between two isolated populations of the same species.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".