Age, growth, and population assessment of grass pickerel (<i>Esox americanus vermiculatus</i>) in two northern populations
Bibliographic record
Abstract
Age assessment was conducted on the at-risk grass pickerel (Esox americanus vermiculatus Lesueur, 1846) in southern Ontario, Canada (the northern edge of the species’ range), to better understand population dynamics. Cleithral age assessment revealed different age distributions between two sample years; the first year characterized by old, large individuals and the second year characterized by mostly young of the year. Back-calculated lengths at age were used to develop the von Bertalanffy growth relationships and estimates of ultimate length. Growth rates were substantially faster in the second year, when fewer and smaller individuals were present, suggesting density-dependent effects on growth. A pseudoannulus in the cleithrum, common to this species, was shown by sequential sampling to form in early July at 70% to 80% of the first growth zone and to occur more frequently in slow-growing fish and strong year classes than in faster-growing individuals and weaker year classes. Mortality rates of females were high (26%–46%) relative to other studies and probably resulted from greater abundance of individuals. Compared with cleithra, scale ages after age 1 were consistently underestimated. Calculated length at cleithral age intervals overlapped minimally, suggesting length could be used as a proxy for assessing age of this species in Ontario to avoid lethal sampling.
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 | 0.001 |
| 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 | 0.001 |
| 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".