Modifying effects of a cobble substrate on thermal environments and implications for embryonic development in lake whitefish (<scp><i>Coregonus clupeaformis</i></scp>)
Bibliographic record
Abstract
A laboratory flume was constructed to examine substrate effects on aquatic development. The flume was designed as a once-through system with a submerged cobble-filled corebox. Lake whitefish (Coregonus clupeaformis) embryos and temperature probes were deployed at multiple sites within the cobble and in the open water channel. Embryos were incubated in the flume for two different experimental periods: one to examine substrate impacts during natural lake cooling (37 days: 5 December 2016 to 10 January 2017) and the second to investigate substrate effects while administering a twice weekly 1 h heat shock (51 days: 11 January to 2 March 2017). During incubation, no significant difference was found in the average temperature between locations; however, temperatures were more stable within the cobble. Following both incubation periods, embryos retrieved from the cobble were significantly smaller in both dry mass and body length by up to 20%. These results demonstrate differences between embryos submerged in a cobble substrate and in the open water column, highlighting the need to consider the physical influences from the incubation environment when assessing development effects as part of any scientific study or environmental assessment.
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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 | 0.000 | 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 | 0.000 |
| 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".