Comparison of Solution‐Based versus Laser Ablation Inductively Coupled Plasma Mass Spectrometry for Analysis of Larval Fish Otolith Microelemental Composition
Bibliographic record
Abstract
Abstract Otolith microchemistry has become a widely used tool for fisheries‐based research in marine systems. However, its application to systems without well‐defined juvenile nursery areas in which distinct otolith elemental signatures can develop (i.e., most freshwater systems) remains limited. In large part, this deficiency is due to unsuitable protocols for reliably processing and analyzing small otoliths of larvae. Herein, we evaluate the abilities of solution‐based (SO) and laser ablation (LA) inductively coupled plasma mass spectrometry (ICPMS) to quantify the otolith elemental composition of larval yellow perch Perca flavescens captured in three distinct spawning locations in Lake Erie (USA–Canada). Analysis of otolith pairs by each technique demonstrated that both SO‐ and LA‐ICPMS could be used to reliably quantify the more abundant elements, such as Sr and Ba. Magnesium and zinc, analyzed by use of both SO‐ and LA‐ICPMS, also met the criteria for inclusion in our analyses (i.e., the coefficients of variation of standards were <10.5%, and over 90% of samples were above detection limits at a single location). Upon closer inspection of the data, however, we found that estimates of Mg and Zn were only reliable for LA‐ICPMS. Estimates of these two elements using SO‐ICPMS were unrealistically high, probably owing to contamination during the otolith dissolution and handling phases. We also found that LA‐ICPMS provided more precise estimates than did SO‐ICPMS for nearly all elements explored, but LA‐ICPMS was somewhat limited by high limits of detection for some elements. Despite these differences, both techniques could accurately discriminate among larvae produced in different Lake Erie spawning locations, primarily because of the significant variation in Sr among larval otoliths. Ultimately, although both methods are appropriate for analysis of otoliths from larvae, we recommend the use of LA‐ICPMS in future otolith microchemical applications involving larvae.
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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 | 0.001 | 0.001 |
| 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".