Ultrasonographic sex identification of Largemouth Bass and Smallmouth Bass
Bibliographic record
Abstract
ABSTRACT Objective Intersexual variation within fish species can be observed through morphological, physiological, and behavioral differences. Although this variation can have important implications for the ecology and management of many fish species, challenges associated with the methods to determine sex have been a limitation for research in this area. This study evaluated the feasibility of portable ultrasonography as a noninvasive tool to determine sex for two monomorphic black bass species, the Largemouth Bass Micropterus nigricans and Smallmouth Bass M. dolomieu. Methods Sex was estimated for wild black bass (n = 123) by using portable ultrasonography and was verified by laboratory dissection to assess accuracy. Our investigation also included a case study involving age-3 tank-raised Smallmouth Bass that were exposed to nonnatural photoperiod and temperature conditions. Results Ultrasonography proved effective for sexing black bass, achieving an accuracy of 92.7%. Mature ovaries were readily identifiable through sonograms, whereas mature testes in males were more challenging to detect. The technique also showed potential for accurately sexing tank-raised Smallmouth Bass. Conclusions Portable ultrasound is a rapid, accurate, and noninvasive tool for the sex identification of black bass, supporting its integration into field and laboratory studies. The methods described in this study should be evaluated in other monomorphic species and may contribute to the effective management of fish populations.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".