Study of natural bitumen of Nagornoye deposit, Troitskneft JSC (the Republic of Tatarstan, Russian Federation) aimed at processing options determination
Bibliographic record
Abstract
© 2014, Canadian Center of Science and Education. All Rights Reserved. The cost of natural bitumen production at present is very high and 3-5 times exceeds the cost of conventional oils production; the technology developers are facing the challenge of developing processes which allow producing high sale price products at a low cost. The present study was aimed at finding out the composition and properties of natural bitumen from Nagornoye deposit of the Republic of Tatarstan (JSC Troitskneft) to determine the possible ways for its processing as well as to definite the processing options. A conclusion made, that the production of residual bitumen of the high-viscosity oils and natural bitumen of Tatarstan Republic (as well as any other region having raw materials with similar composition) will contribute to increase in their production volume and quality by means of compounding of residual and air-blown bitumen, as in this particular case their advantages are combined. In addition, this will contribute to solution of the problem related to introduction of water-bitumen emulsions and bitumen-polymer binders into the road construction of Tatarstan Republic. The use of natural bitumen for production of various commercial bitumen marks and various bitumen products, makes its recovery economically feasible as its conventional recovery and transportation is noncompetitive against conventional oils. At the same time, profitability of a pure bitumen option can be increased by means of a bitumen-fuel option, provided that the diesel fraction is brought in full compliance with the GOST for S (summer), W (winter) and A (arctic) marks of diesel fuel.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".