Accuracy of histology, endoscopy, ultrasonography, and plasma sex steroids in describing the population reproductive structure of hatchery‐origin and wild white sturgeon
Bibliographic record
Abstract
Hatchery-origin white sturgeon Acipenser transmontanus in the lower Columbia River, Canada are approaching puberty, and describing the reproductive structure of the population is critical to determine if they are capable of contributing to spawning events in the wild, a key management uncertainty. Few studies have compared the accuracy of available tools (histology, ultrasound, endoscopy, and plasma sex steroids) used to assign sex and stage of maturity within the same population of prepubertal and post-pubertal sturgeon. Population reproductive structure was described using these tools in 332 hatchery-origin and 75 wild individuals over 2 years (2017 and 2018). True sex was determined using histological analysis of gonadal tissue, which is 100% accurate at assigning sex and stage of maturity in fish when germ cells are present in the biopsy. All hatchery-origin fish assessed had not reached puberty and were pre-meiotic males (n = 158) or pre-vitellogenic females (n = 174). Assignment of true sex using histology was 97% in hatchery-origin and 94% in wild fish as several biopsies did not contain germ cells. Fish with gonadal biopsies that did not contain germ cells and intersex fish (n = 3) were not included in further analyses of other tools. Accuracy in assigning sex to both the hatchery-origin (98%) and wild (100%) fish was highest using endoscopy (an otoscope). The other tools evaluated were less accurate, with 69% accuracy in hatchery-origin and 74% accuracy in wild fish for plasma sex steroids and 57% accuracy in hatchery-origin and 70% accuracy in wild fish for ultrasonography. Based on these results, endoscopy was the most reliable tool for assigning sex in both prepubertal and post-pubertal fish and can be easily complimented with histology when determining stage of maturity or describing population reproductive structure.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".