Study on the safety management of toxic gas cylinder distribution using RFID
Bibliographic record
Abstract
The usage of toxic gas has increased consistently by the needs of the high-tech industry. Unfortunately, the number of toxic gas accident has also increased and it might cause huge human and material damage which is occurred by toxic gas leakage and diffusion. Mainly, toxic gases are stored in cylinders, however, there is a high probability of abusing to terrorism for toxic gas cylinder and operators dealing with toxic gas manage their toxic gas cylinder individually. For these reasons, toxic gas cylinder needs tracking management on a national level. In this study, it suggests that the tracking management system of toxic gas cylinder using RFID (Radio-Frequency identification), which is able to handle systematically by data integrating with equal cylinder distribution in each company. It is essential that the data integration system of toxic gas cylinder must establish a standardized ID on each cylinder and manage the history of cylinder distribution on existing each system. This system is operating preliminarily on the three sites to verify. It is expected that accidents caused by terror will be dramatically reduced and the most advanced level of safety control will be achieved.
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 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 | 0.003 | 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 | 0.001 | 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".