Use of portable ultrasonography to determine ovary size and fecundity non-lethally in northern pike (Esox lucius) and white sucker (Catostomus commersoni)
Bibliographic record
Abstract
The objective of this study was to investigate the feasibility of using field-based portable ultrasonography to accurately estimate ovary weight, gonadosomatic index (GSI) and fecundity in large-bodied fish species. These reproductive endpoints were estimated using ultrasound on prespawning female northern pike (Esox lucius) and white sucker (Catostomus commersoni) and compared with actual measured values determined post mortem. Using five cross-sectional ultrasound images in pike, estimated ovary weight and fecundity, but not GSI, were significantly correlated with measured values. All endpoints were overestimated by 21 to 23% using ultrasound in pike. In a subsequent experiment using 20 cross-sectional ovary images, estimated ovary weight, GSI and fecundity were significantly correlated with measured values in white sucker. Although underestimated by 5 to 12% using 20 cross-sectional images, there were no statistical differences among estimated and measured mean ovary weight, GSI and fecundity in white sucker using this approach. Based on the variances for GSI estimations in both species, power analysis indicated that the ultrasound technique could detect a 25% change in GSI using sample sizes of <20 fish. This study illustrates the utility of portable ultrasonography as a promising non-lethal technique for assessing reproductive endpoints in the field.
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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 | 0.000 | 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".