Investigation of size and shape differences depend to sex, age and season on scales of smallmouth lotak (Cyprinion kais)
Bibliographic record
Abstract
In this study, a total of 82 (49♀♀, 33♂♂) Cyprinion kais samples from the same location in the river of Tigris were collected and ages of scales taken from front and upper section of lin lateral of dorsal fins of fishes were determined and photographed by an Olympus digital camera with Canon SX7 model binocular under the same conditions and then six landmarks were taken by using tpsDig ver. 2.32 software. Afterwards, procrustes analysis was conducted. After separating shapes and sizes, ANOVA, PCA, CVA/MANOVA and DFA analyses were performed. According to the results of the analyses, there was a significant difference between the samples in terms of gender and size (Size ANOVA: F= 50.6, p<.0001); at the same time the difference between samples in terms of shape was at the level of (Shape ANOVA: F= 3.92, p =0.0002); there was a significant difference between samples at different ages in terms of size (Size ANOVA: F= 44.08, p<.0001), however, no difference was found in terms of the shape of the samples; there was a significant difference between size (Size ANOVA: F= 17.87, p<.0001) of the samples but no difference was found between shape of them depending on the season. For gender, age and seasons, the first two components explain 61.4%, 63.6% and 63.4% of total variance, respectively. As a result, there was a difference between sizes of the C. kais species depending on gender, age of the fishes and the season; however, although there was a difference between shapes of the samples depending on gender variable, no difference was found depending on age of the fish and the season.
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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 | 0.002 | 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 | 0.001 |
| 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 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".