Advances and discussion about the study on deep basin gas in western Sichuan province depression
Bibliographic record
Abstract
Western Sichuan province depression has geological conditions similar to Alberta basin of Canada in which deep basin gas most probably was formed . However, detailed study showed that the intensity of structural reversion, pressure attributes of gas-bearing strata, and the time of gas generation of source rocks of these two basins are quite different. So it is not reasonable torta basin. For the purpose of studying the accumulation mechanism and distribution discipline of gas reservoirs of western Sichuan province depression, it will be better to start with practical geological conditions of that depression, rather than to simply compare it with an available model. It is thought that the gas pools in western Sichuan province depression have the feature of reversed gas-water contact. As only a few data of formation pressure are available, this point of view needs further study. It is considered that the fault system in western Sichuan province depression has a strong influences on the accumulation of deep basin gas pools, and has led to a peculiar distribution pattern of deep basin gas in that basin.It terms of comprehensive study of the controlling factors including burial depth of source rocks, organic matter maturity, gas generation intensity, reservoir property, structural pattern, etc., a rough prospecting of deep basin gas distribution of western Sichuan province depression was made.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".