Bibliographic record
Abstract
North America is in the midst of an energy revolution 1 —centered on unconventional petroleum (i.e., oil shale and oil sands) and unconventional natural gas (i.e., gas shale). Unfortunately, this revolution threatens to completely unhinge the global climate. 2 This concern is especially acute with the Canadian oil (or tar) sands. The Canadian tar sands are a high carbon substitute for crude oil (i.e., conventional petroleum). 3 (The Canadian oil sands are reputed to hold 170 billion barrels of petroleum. 4 ) Bringing the oil sands to market significantly contributes to the global warming phenomenon in two ways. 5 First, oil sands are “processed” onsite. Oil sands (a.k.a. bitumen) is diluted into dilbit (diluted bitumen) for purposes of transportation, and this requires energy—which results in greenhouse gas emissions. 6 Second, apart from the energy used to make the oil sands transportable, more energy is needed to refine the tar sands into end use products (e.g., jet fuel) than is used to refine most conventional crude. The extra energy required to refine oil sands results in additional greenhouse gas emissions. 7
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".