The interpretation of background variation in regional geochemical surveys – an example from Nunavut, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In glaciated terrains, geochemical maps portray bedrock provenance and the integrated effects of glacial processes affecting the distribution, concentration, and partitioning of minerals in sediments. In those maps, indicators of economic mineralization can be difficult to distinguish in the context of natural background, especially at low trace metal concentrations. Sample mineralogy, which can be inferred from lithophile elements, provides a key basis for interpreting sediment provenance and controls on background variation in metal concentrations. In non-carbonate terrain, the principal rock-forming minerals digested by aqua regia are Mg-bearing phyllosilicates, including trioctohedral chlorite, biotite, and phlogopite. Hence, Mg analyses directly reflect the concentrations of those minerals. In a regional geochemical survey of till in Nunavut, strong linear correlations ( r >0.840, n =1842, p <0.0001) for Cu and Cr with Mg concentrations indicate Mg-bearing phyllosilicates are the principal metal hosts, and that the metals are bound in mineral lattice structures in direct proportion to Mg. Thus, metal:Mg ratios express geochemical properties of the mineral(s) hosting the metal, and are independent of mineral partitioning among size fractions that results from either glacial or postglacial processes. Ratio maps can be used to establish till provenance and infer aspects of bedrock composition not evident in single-element geochemical maps. Ratio anomalies could indicate metals derived from economic indicators such as sulphide minerals, and metal-rich particulate from anthropogenic sources .
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it