Cross-tributary analysis of parr to smolt recruitment of Atlantic salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
We used estimates of Atlantic salmon (Salmo salar) parr and smolt density, estimated in three tributaries of the West River, Vermont, U.S.A., to determine (i) if smolt recruitment is density dependent or independent of parr density, (ii) if the proportion of parr migrating as smolts and cohort survival differ among tributaries, and (iii) the effect of parr maturity on smolt production and recruitment variability. We found that parr to smolt recruitment was best described with a linear function providing no evidence for density dependence in the recruitment dynamics of parr and smolts at the tributary scale. The proportion of age-1 parr recruiting to age-2 smolts did not systematically differ among tributaries or years (overall mean ± 95% CL: 18 ± 11%, range = 9-37%), and mean age-1 to age-2 survival ranged less than twofold among tributaries (27-46%) and was independent of cohort density. Survival of age-1 mature (39%) and immature (33%) parr was similar, but probability of smolting for mature parr (0.21) was threefold less than for immature parr (0.76). Quantifying smolt recruitment pathways involving parr maturation helped elucidate the population-level effect of parr maturation on smolt production and recruitment variability.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".