Comparison of geochemical data derived from till and lake sediment samples, Labrador, Canada
Why this work is in the frame
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Bibliographic record
Abstract
Techniques for combining geochemical data from a till survey (2438 samples) and a lake sediment survey (17 447 samples) are assessed to determine a rigorous method for comparing the two sampling media. This study is based on five elements, (Cu, Ni, Fe, Pb and Zn) from overlapping geochemical surveys in Labrador, Canada. Two methods for comparing the till and lake sediment geochemical data are: (1) gridding and (2) nearest neighbour. Pearson correlation coefficients between media are low (<0.2) for Cu, Fe and Zn and only Ni has a correlation significant at the 95% confidence level (r 2 = 0.45). Results from gridding show slightly higher correlations. Differences are most evident at the extremes, as anomalously high element concentrations in one medium typically do not correlate with high values in the other medium. Correlations between media increase as distance decreases for Ni, Pb and Zn; however, no such trend is evident for Cu or Fe. The nearest neighbour method has several advantages: this procedure retains the original data and it permits calculation of statistics such as distance and direction between the points. The differences between the geochemical results from the two media highlight the synergistic value of multi-media geochemical sampling.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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