Using Mg as a Proxy for Crystal Structure and Sr as an Indicator of Marine Growth in Vaterite and Aragonite Otoliths of Aquaculture Rainbow Trout
Bibliographic record
Abstract
Abstract Otoliths of rainbow trout Oncorhynchus mykiss reared in marine cages were analyzed by laser ablation‐inductively coupled plasma mass spectrometry to determine their Sr and Mg concentrations and by micro‐Raman spectrometry to assess mineralogy. Analyses of transects from the core of the otolith to the growing edge (incorporating otolith material produced during freshwater hatchery and marine cage growth) revealed that these transects were composed of aragonite, vaterite, or both. The concentration of Sr varied significantly between mineral polymorphs and environments (hatchery or marine). In vaterite transects, Sr concentrations increased an average of 130 μg/g between freshwater hatchery growth and marine growth. This increase represents a near doubling of the Sr concentration in vaterite and made Sr a suitable indicator of a change in the environment as reflected in vaterite transects. In aragonite transects, Sr concentrations increased an average of 1,330 μg/g between hatchery and marine growth, which simplified the identification of the timing of marine transfer. The concentrations of Mg also varied significantly between mineral polymorphs, the difference in the average concentration between aragonite and vaterite being 1,179 μg/g. This allowed for the use of Mg as a proxy for mineralogy. While there was an increase in Mg concentration between hatchery and marine growth in some vaterite otoliths, the change was small compared with the change as a result of mineralogy. The average aragonite‐vaterite partition coefficients were 5.238 and 8.096 for Sr and 0.057 and 0.128 for Mg for hatchery and marine growth, respectively.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".