Predicting the classification characteristics of coal. Part 2. Maximum moisture content
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
Analysis of 63 samples of coal concentrates (from Ukraine, Russia, the United States, Canada, Australia, and Poland) currently employed at Ukrainian coke plants indicates that the prediction of the maximum moisture content of coal may expediently be based on R o and Q , determined, respectively, in plant laboratories and in power-station laboratories. The maximum moisture content of metamorphically distinct coals does not depend on their ash content (in the range 3.7–35.3%) nor on the chemical composition of the ash, expressed by the basicity index B b (in the range 1.24–27.18) and the base/acid ratio I b (in the range 0.198–1.832). Although the oxidation of coal also increases the maximum moisture content, this change is less than the error in its determination (0.5%). The oxidation of practically 30% of the coal’s organic mass increases the maximum moisture content by no more than 0.4%
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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) | 0.000 | 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