Bibliographic record
Abstract
The northern water snake, Nerodia sipedon and the queen snake, Regina septemvittata, are two species of the subfamily Natricinae that occur sympatrically throughout much of their ranges in Ohio.Regina septemvittata does not appear to be as abundant as it once was in much of its range, and published natural history information is lacking.Nerodia sipedon, however, has exhibited no decrease in abundance, and there is a relative abundance of published natural history information on this species.This study compares growth and population size for both species utilizing mark-recapture techniques and skeletochronology at the Sandusky Bay Fishing Access Site in Ottawa County, Ohio.The Sandusky Bay fishing access site supports populations of the following snake species: the northern water snake, Nerodia sipedon, the queen snake, Regina septemvittata, the eastern garter snake, Thamnophis sirtalis, Butler's garter snake, Thamnophis butlerii, the eastern fox snake, Elaphe gloydi, and Dekay's snake, Storeria dekayi.Population estimates for Nerodia sipedon result in densities similar to published values for nearby populations.Population estimates for Regina septemvittata displayed a decline over the course of the study, which was mirrored in the relative abundance of queen snake within the total sample for each year.Growth has an impact on snake conservation through delayed maturation, longer time spend at a size class experiencing a higher rate of mortality, and reduced reproductive advantage.Nerodia sipedon is growing faster than most of the previously published rates, and growth rates are similar to those experienced in Lake Erie populations since the introduction of the round goby.Regina septemvittata females and juveniles are growing slower than the previously published values.iii Skeletochronology was used to age individuals via lines of arrested growth (LAG) in bones.Tail vertebrae were sampled in an attempt to age individuals of both Nerodia sipedon and Regina septemvittata.There was no correlation between snout-vent length and number of LAGs.There was very little agreement between multiple investigators with respect to the number of LAGs counted within a single sample.The results of this study suggest an overall decline in the queen snake, Regina septemvittata and a stable population of the northern water snake, Nerodia sipedon, at the Sandusky Bay location.The difference in growth rates between this study and previously published values for both species may be influenced by the introduction of round gobies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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 teacher head, 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".