Bibliographic record
Abstract
Among the many sulfides in petroleum exploitation,H2S ocuppies the major ratio.Heavy reservoir accompany H2S gas,and thermal recovery technology will accelerate H2S production and density rising.Because H2S make olfactory nerve paralysis,it is not easy to flari odor,which lead to the occurance of lightning intoxication death and cause great harm.During petroleum exploitation applying general protection technique and carrying out new efficiency desulfurizer and high efficiency absorption sulphur fixing agents device,have important practical significance.Study and drew on Canada Oilfield protection experience of H2S,and bulid our country work licensing system of oil and gas wells contained H2S.A deep lesson should be learned from the major accident happened in 12·23 ChongQing Kai xian LuoJia's 16H gas well blowout due to the lost control and hydrogen sulfide poisoning.During exploiting oil and gas wells contained H2S,only earnestly taking safety education and alarm of protection H2S,fulfiling countermeasure of protection H2S,setting down detailed emergency response plan of accident,and organizing regularity emergency drilling,the purpose of avoiding the potential danger can 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 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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".