Quantification of SEM microtextures useful in sedimentary environmental discrimination
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
Scanning electron microscopic imagery is often used to identify and discriminate among environments of sedimentation with the main aim of identifying individual microfeatures, or suites of microtextures, that are considered indicative of a particular depositional environment or geologic process. Because few microtextures are considered to represent a single geologic process it is necessary to analyze a large number of quartz sands and other mineralic grains with the objective of determining the frequency of occurrence of a range of microtextures within a distinct sample suite. Using percent frequency of occurrence of different microtextures from suites of fluvial, glaciofluvial and glacial sands from sites in Estonia and Latvia, we invoked statistical comparison of different sample suites using Euclidean distances. These provide a quantitative means of measuring the differences among different sediments and processes that formed them and also a quantification tool useful
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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