Construct a Paleo-Limnological Environment Based on Coal Petrography; Case Study, Two Selected Coal Seams, North Crowsnest Open-Pit Mine, Canada
Bibliographic record
Abstract
The Crowsnest coalfield is a separated structural coalfield at the East Kootenay basin within southeast British Columbia. Selected Jurassic-Cretaceous two coals seam S-10 and S-C of the Mist-Mountain formation were investigated from the points of coal petrography to construct a Paleo-limnological setting. Twenty-two channel coal samples were assembled and measured from S-10 and S-C coal seams. Vitrinite reflectance measuring of the S-10 coal concern to low-volatile bituminous (1.61, on average). While the vitrinite reflectance measurements of S-C coal seam show an average value of 0.98 related to high-volatile bituminous. Petrographic analysis demonstrates that the S-10 coal seam appears to be rich in inertinite than the S-C coal seam that appears rich in vitrinite. Applying coal facies indices of Tissue Preservation Index, Gelification Index, Ground Water Index Vegetation Index and coal facies diagrams for the studied coal seams aid to suggest a condition of the depositional Paleo-environments. The results promote Paleo-depositional sites of telmatic to limno-telmatic setting of rheotropic systems swamp. The obtained results show a trend of increase in both herbaceous flora and anoxic waterlogged limo-telmatic setting toward the younger coal seam S-C than the older S-10 coal seam.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".