Elemental analysis of otoliths, fin rays and scales: a comparison of bony structures to provide population and life‐history information for the Arctic grayling (<i>Thymallus arcticus</i>)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract – We used laser ablation inductively coupled plasma mass spectrometry line scans to determine the elemental composition of otoliths, pectoral fin rays and scales of Arctic grayling. Elemental signatures of otoliths and pectoral fin rays effectively provide life‐history information on individual fish, important for management of grayling, and potentially all freshwater teleosts. Bulk elemental signatures measured in the otoliths and fin rays were highly correlated to the stream chemistries where the fish were captured. A surprising result of this study was that fin rays showed the strongest relationship with water chemistry for strontium. Scale strontium concentrations were not correlated to water chemistries suggesting that other physiological mechanisms, or remobilisation, may be influencing the deposition of trace elements within scales. Linear discriminant function analyses for otolith and fin ray elemental signatures (and intriguingly also for scales) separated fish from different rivers for all three structures; thus, this technique can be used effectively as a means to discriminate origin of capture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it