A New Incubator for the Assessment of Hatching and Emergence Success as Well as the Timing of Emergence in Salmonids
Bibliographic record
Abstract
Abstract We devised a new incubator to estimate hatching and emergence success as well as the timing of emergence of brook trout Salvelinus fontinalis. The incubation basket is cylindrical and made of a polyvinyl chloride (PVC) grid that allows water to flow through from all directions. A fry trap is set on top of the incubation basket to catch the emergent larvae. A PVC coupler is fixed to the incubation basket and allows the fry trap to be easily removed and replaced so that one can sample larvae during emergence. In the field, the emergence success for incubators containing natural substrate ranged from 0% to 50%, compared with 0% to 77% for incubators that used Astroturf as a substrate. In the laboratory, the emergence success with Astroturf alone (75%) was comparable to that in the incubators that used Astroturf in the field (73%), suggesting that the incubator structure itself does not influence the survival of brook trout eggs. This incubator is easy to build and the materials needed for its construction are readily available. The collection of emergent larvae is easy and does not require additional equipment. Its advantages over other salmonid incubators are that it can resist adverse spring floods and freshets and it allows the assessment of emergence at various times in the field. This is important when determining the timing of emergence.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".