Clast rind analysis using multi‐high resolution instrumentation
Bibliographic record
Abstract
Clast weathering rinds, formed over varying lengths of time (10(2) -10(6) years) in terrestrial environments, are measured to provide relative ages for deposits in glacial sequences, specifically to differentiate between glaciations, occasionally within glaciations. Other studies have sought to reveal weathering rates in non-glacial environments using microscopic techniques and isotopes. Recent analyses of clast rinds from tropical, mid-latitude and polar areas reveal an astounding corpus of organic and inorganic paleoenvironmental data derived from atmospheric and biospheric elements active in weathering clasts in glacial deposits over varying lengths of time. In some cases, extreme biochemical products, observed within the rind matrix, are seen to play a role in adjusting redox potentials important in the production of oxides and hydroxides and biominerals with variable compositions. Up to recently, rind analysis has been limited to use of the light microscope and SEM/EDS, which has greatly advanced our understanding of compositional inter-linkages of minerals and biotic elements, but only along horizontal axes within the rind. A test involving rind surface composition using vertical axis nanospaced layer analysis within rinds using focused ion beam (FIB) and TEM/STEM/EDX imagery and chemistry illustrates the power of data acquisition within the three-dimensional weathered archive. SCANNING 38:202-212, 2016. © 2015 Wiley Periodicals, Inc.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".