Using fin ray elemental signatures and growth zone width to estimate onset of sexual maturity in lake sturgeon (<i>Acipenser fulvescens</i>)
Bibliographic record
Abstract
Characterizing inter- and intra-population levels of variability in age at sexual maturation for long-lived fishes provides insight into year-class strength and recruitment dynamics, allowing for more effective management practices. Here we analyzed the ontogenetic chronology of pectoral fin ray annuli trace elemental concentration profiles as well as changes in annuli growth in lake sturgeon ( Acipenser fulvescens) to determine onset of sexual maturity (OSM). Elemental concentrations and growth-zone width were used to build a random forest classification model to discriminate year-specific signatures to before or after OSM from 98 individual fin rays from both sexes across multiple populations and watersheds. The model demonstrated an overall accuracy of 98.8%. Ba was the most important variable related to OSM discrimination success followed by zone width, Pb, Mn, Mg, Zn, Cu, and Sr. Fin ray elemental concentrations began to increase at approximately age 24 (±4.7 years) in females and 15 (±3.1 years) in males while zone width decreased. This study implies that new applications for fin ray microchemistry are possible and could benefit future fisheries management strategies specifically by adding nonlethal or less invasive sampling techniques for evaluating OSM in sturgeon.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".