Bibliographic record
Abstract
Gas content measurement is a common technique in the prevention of coalmine gas disasters. During the measurement, the gas desorption amount of field coal samples needs to be obtained by an instrument working under the principle of gas collection by water displacement (GCWD). The instrument is poorly automated, and susceptible to the influence of subjective factors. To overcome these defects, this paper designs an automatic detector of gas desorption, aiming to realize automated detection. Firstly, the authors analyzed the gas desorption detection process, and clarified the contents and features of the information to be collected. On this basis, the hardware and software systems of the multi-data automatic detector were developed based on digital circuit design and multi-sensor detection. To further improve the measuring accuracy of gas desorption, the multi-range multi-stage mode was introduced to the automatic detector. Application results show that the proposed detector can automatedly collect and store gas desorption amount, ambient pressure, and temperature, greatly improve the degree of automation, and minimize the influence of subjective factors. The popularization of this detector will make gas desorption measurement more efficient and effective, laying a solid basis for the prevention of coalmine gas disasters.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".