Characterization of raft mussels according to total trace elements and trace elements bound to metallothionein-like proteins
Bibliographic record
Abstract
In the current work, samples of Mytilus galloprovincialis collected in different sites from Ría de Arousa estuary (Galicia, north-western Spain) were analysed for total Al, As, Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn, and for Ba, Cu, Mn and Zn bound to metallothionein-like proteins isoform I (MLP-I) contents. Inductively coupled plasma-optical emission spectrometry (ICP-OES) was used to assess total metal contents in raft mussels, while high performance liquid chromatography (HPLC) with an on-line metal detection with ICP-OES was used to measure metals bound to MLP-I. A microwave assisted acid digestion procedure was used as a sample pre-treatment for total metal contents, while a cytosolic preparation method based on a blending procedure with TRIS-HCl (pH 7.4) as an extracting solution was used to isolate MLP-I. Concentrations of total metals and metals bound to MLP-I were used as discriminating factors to establish different regions in the Ría de Arousa estuary. Principal component analysis (PCA) and cluster analysis (CA) were used as unsupervised pattern recognition procedures, and the half-range central value transformation was used as a data pre-treatment to homogenize data sets. Results have revealed a separation of raft mussels in good agreement with water circulation pattern and oceanographic processes in the estuary only when concentrations of metals to bound MLP-I are used as discriminating factors. Otherwise, raft mussels are classified as samples harvested in the inner or outer sides of the Ría.
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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 | 0.001 | 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 | 0.001 |
| 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".