Geochemistry of Sediments and Sedimentary Rocks: Evolutionary Considerations to Mineral Deposit- Forming Environmentsby David Lentz (ed.), Geological Association of Canada, GeoText 4, 2004, 184 pp. US$80. ISBN 0-919216-76-5
Bibliographic record
Abstract
How can geochemistry be applied to our understanding of the formation and evolution of sedimentary rocks and sedimentary basins? Collectively, the ten papers included in this book address this question and suggest that geochemistry is important for (a) understanding changes that take place in the diagenetic environment, (b) interpreting provenance and developing crustal evolutionary models, (c) dating sedimentary rocks, and (d) understanding the genetic relationships between sedimentary ore deposits and their associated sedimentary sequences. The introduction by David Lentz is a good historical perspective and review of the use of geochemistry in sedimentary rock research that provides perspective for the more data-specific papers that follow. However, a clearer picture of the primary goals of the book and how the papers were chosen would have been useful to help a reader understand the common theme that threads the papers together. The paper by S. McLennan et al. shows the significance that geochemistry can …
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".