Origin determination of the Eastern oyster (<i>Crassostrea virginica</i>) using a combination of whole-body compound-specific isotope analysis and heavy metal analysis
Bibliographic record
Abstract
Various samples of the Eastern oyster, Crassostrea virginica, were collected from five harvest bay areas in the Gulf of Mexico coastal waters of Florida (FL), Louisiana (LA) and Texas (TX). Cadmium and lead concentrations from the extracted whole-body soft tissues were analyzed by inductively coupled plasma-mass spectrometry (ICP-MS), and bulk δ13C and δ15N isotope ratios and amino-acid-specific δ13C values were analyzed via isotope ratio mass-spectrometry (IRMS). The combined data was subjected to multivariate statistical analysis to assess whether oysters could be linked to their harvest area. Results indicate that discriminant analysis using the δ13C values of five amino acids-serine, glycine, valine, lysine and phenylalanine-could discriminate oysters from two adjacent harvesting in Florida with 90% success rate, using leave-one-out cross validation. The combination of trace elements and isotope ratios could also predict geographic provenance of oysters with a success rate superior to the isolated use of each technique. The combinatory approach proposed in this study is a proof-of-concept that compound specific stable isotope analysis is a potential tool for oyster fisheries managers, wildlife, and food safety enforcement officers, as well as to forensics and ecology research areas, although significantly more work would need to be completed to fully validate the approach and achieve more reliable statistical results.
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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".