HEAVY MINERALS OF THE EAST-CENTRAL BERING SEA CONTINENTAL SHELFI, 2
Bibliographic record
Abstract
ABSTRACT: A factor analysis of 51 grab samples from the east-central Bering Sea con-tinental shelf identified three factors that account for 88 % of the variation in the relative amounts of the nine major heavy mineral groups that were used as variables. The most important components for definition of the sources and processes which have determined the properties of the surface sediments in this area are epidote, garnet and opaque minerals, and clinopyroxene and weathered grains, for Factors I-III, respectively. The occurrences and textural associations of Factor I- I I I sediments indicate that the relative fractions of the characteristic minerals have been largely determined by sorting; proximity of source is more important along the Alaskan mainland. Throughout he area, the heavy mineral contents of samples differ from those of modern Yukon River sediments. This study demonstrates the utility of factor analysis in the interpretation of relatively uniform heavy mineral data.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".