Age, Growth, Survival, and Maturity of Lake Trout Morphotypes in Lake Mistassini, Quebec
Bibliographic record
Abstract
Abstract Life history characteristics (age, growth, survival, and maturity) were compared between the deepwater “humper” and shallow‐water “lean” forms of lake troutSalvelinus namaycushin Lake Mistassini, Quebec, to determine whether the two morphotypes may represent resource polymorphism. Lake trout were sampled using graded‐mesh (range = 51–114 mm stretch) gill nets set in deep and shallow waters. Humpers were typically caught in deep waters (>50 m) and averaged 474 mm TL (range = 389–616 mm) and 852 g in weight (range = 470–1,710 g), whereas leans were typically caught in shallow waters (<50 m) and averaged 525 mm TL (range = 301–865 mm) and 1,210 g in weight (range = 200–6,500 g). Humpers and leans did not differ in weight–length relationships and grew slimmer with length over a common TL range (389–616 mm). Average age of humpers was 27 years (range = 13–49 years); average age of leans was 21 years (range = 6–42 years). The two forms did not differ in total annual mortality (A) of fish older than 17 years, the first age beyond which numbers declined with age for both morphs (A= 5.1%; 95% confidence interval = 2.4–7.8%). Humpers grew slower (annual growth rateω= 53 mm/year) than leans (ω= 68 mm/year) and to a shorter mean asymptotic length (L∞= 514 mm) than leans (L∞= 605 mm). Mature humpers (mean TL = 475 mm, SE = 9.0;N= 58) were shorter on average than mature leans (mean TL = 539 mm, SE = 8.5;N= 65); mature humpers (mean age = 27 years, SE = 1.0;N= 56) were also older on average than mature leans (mean age = 23 years, SE = 0.98;N= 61). We conclude that lean and humper forms of lake trout in Lake Mistassini differed in age, growth, and maturity; this is consistent with the resource polymorphism that has been observed for other lake trout populations and other char species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".