Nonlethal Sampling of Sunfish and Slimy Sculpin for Stable Isotope Analysis: How Scale and Fin Tissue Compare with Muscle Tissue
Bibliographic record
Abstract
Abstract We found that the sampling of tissues that do not result in the death of the fish, such as scale and fin tissue, may be substituted for muscle tissue in stable isotope analysis (SIA) of fishes. Comparisons were made between the values of δ13C and δ15N found in muscle tissue with the corresponding scale tissue of three sunfish species (bluegill Lepomis macrochirus, pumpkinseed L. gibbosus, and redbreast sunfish L. auritus) and with caudal fin tissue of slimy sculpin Cottus cognatus. The fish showed strong linear correlation in δ13C values between their nonlethally sampled scale or fin tissue and their muscle tissue (combined sunfish: r = 0.97; slimy sculpin: r = 0.84). Sunfish δ13C values were higher in scale tissue than in muscle tissue and required a correction factor for converting the scale values to the muscle values (regression equation: y = 1.1673x + 1.0531). Slimy sculpin δ13C fin and muscle values were similar and did not require a correction factor. The correlation of δ15N values between the tissues was also strong in both sunfish (r = 0.94) and slimy sculpin (r = 0.90). A correction factor was needed to convert δ15N values from scale to muscle in the three sunfish species (y = 0.8504x + 2.6698) and from fin to muscle in slimy sculpin (y = 1.2658x − 3.3234). Results of this study and other literature support the use of nonlethally sampled tissues for SIA of fish. These methods may be used for investigations of rare and endangered species and also allow for analysis of archived fish scales.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".