Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Due to high oil prices, and a general decline of world oil reserves structure, more and more attention is paid to the development of new production technologies of hardhydrocarbons extraction.In Canada bitumen oil reserves exceed the oil reserves of Saudi Arabia.In this country the technology of tar sands development is being developed.One of the ways that became a tradition is extraction of tar sands from an open pit followed by treatment with hot water to separate oil from it.Another commercially successful way, is the SAGD method, which involves drilling pairs of horizontal wells and steam injection into the well located in the formation 5 meters above the other (SAGD: upper horizontal well is used for steam flooding and creating of high temperature vapor chamber.The process begins with the stage of the prehating, during which (a few months) the steam circulations in both wells.Thus due to conductive heat transfer there is a heating of a formation area between the production and injection wells.Oil viscosity is reduced in this area, providing hydrodynamic connection between the wells.At the main production stage the steam injected into the injection well.The injected steam, due to the difference of densities makes its way to the top of the producing formation, creating the steam chamber increase in size.At the surface of the division between the vapor chamber and cold net oil thickness there is a continuos heat exchange process, whereby the steam condenses into water and heated together with oil flows down to a producing well under the influence of gravity.Growth of the steam chamber continues until it reaches the roof of the formation whereupon it begins to expand outward.While this oil is in contact with the high temperature steam chamber).
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 it