Relationship between average maximum and average arbitrary reflection values of coals vitrinite
Bibliographic record
Abstract
For a quantitative assessment of the degree of coalification of coals in different countries, either average arbitrary (R0,r) vitrinite reflectance or average maximum (R0,max) vitrinite reflectance are mainly used. Since these indicators differ markedly in magnitude, in many countries, equations of the relationship between them have been established relatively long time ago in order to compare correctly the technological properties of different coals of the same type by indicators R0,max or R0,r. For Russian coals, the relationship between the vitrinite reflection indices R0,max and R0,r has not yet been established. Based on the studies of 40 samples of coals from Russia (Kuznetsk Basin), equations of the relationship between the average maximum (R0,max) and average arbitrary (R0,r) reflection values of coals vitrinite were obtained, taking into account the degree of their genetic recovery. The accuracy of calculating the indicator R0,max through R0,r at that is higher when taking into account the degree of genetic recovery of coals, which was 0.03%, versus 0.04% without accounting it. To compare technological properties of Russian coals by the same type of indicators R0,max or R0,r with the coals of Australia, USA, Canada, Poland, Germany, the equations of the relationship between the average maximum (R0,max) and the average arbitrary (R0,r) vitrinite reflectance presented for the coals of these countries according to publications in scientific journals.
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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 | 0.004 |
| 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 | 0.001 |
| 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".