Is Cating's Method of Transverse Groove Counts to Annuli Applicable for all Stocks of American Shad?
Bibliographic record
Abstract
Abstract A scale aging method was reported by Cating in 1953 for American shad Alosa sapidissima in the Hudson River and subsequently validated by recapturing fish marked and released in the Connecticut River. However, American shad spawn in all major rivers from Canada to Florida and their scales record growth events occurring in three distinct biogeographic provinces. Thus, a single scale aging method may not be applicable across the latitudinal range of this species. To address this concern, scales from American shad from one southern river (the St. Johns), three Middle Atlantic rivers (the Delaware, Hudson, and Connecticut), and one northern river (the Merrimack) were examined. Scales were cleaned, impressed in acetate, and analyzed by the same reader using a digital imaging system. The transverse grooves, the key morphological character used in Cating's method, were counted to the distal edge of the freshwater zone and the first three annuli. In most instances, these groove frequencies were statistically different from Cating's data for the Hudson River. Moreover, our data showed enough overlap in groove frequencies that they cannot be relied on as diagnostic characters for the freshwater zone and first three annuli in fish with difficult‐to‐interpret scales. Scale size explained more of the variance in groove frequencies than fish age did. Regardless of the specific process creating transverse grooves, we provide evidence that Cating's method should not be used to age American shad.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".