Risk field assessment of longwall working face by the double-sided roof cutting along the gob
Bibliographic record
Abstract
In order to study the mechanism of the dual side roof cutting technology on the composite disaster of gas and coal spontaneous combustion in goaf, a model for the evolution of porosity and permeability in the dual side roof cutting working face was constructed. The location of the occurrence of the compound disaster of gas explosion and coal spontaneous combustion under the double-sided roof cutting mode was studied, and the sensitivity of the evolution pattern of the compound disaster area to the amount of air supply and gas gush was summarized. The results indicate that the top cutting pressure relief technology significantly reduces the permeability of porous media, and the sensitivity of the goaf on the intake side to airflow disturbances is significantly reduced. As the air supply volume increases, the distance between the gas explosion risk area and the coal spontaneous combustion risk area gradually decreases, and the probability of composite disaster areas is 0. The increase of air supply and gas emission makes the gas concentration in the middle and deep goaf increase in an exponential function, and the width of the gas explosion risk area increases gradually. When the outflow reaches 40 m3/min, there is no composite disaster zone, indicating that the rapid increase in outflow inhibits the occurrence of composite disasters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".