Bibliographic record
Abstract
Seen from a Middle Eastern perspective, the present global oil situation can be summarised within five major and inescapable trends: 1 The world's super giant and giant oil fields are dying off; 2 There are no more major frontier regions left to explore besides the earth's poles; 3 Production of non-conventional crude oil has been initiated at great costs – in Venezuela's Orinoco belt, Canada's Athabasca tar sands and ultra-deep waters; 4 Even OPEC's oil production has its limits; 5 No major primary energy rival can possibly take over from oil and gas in the medium term. Adding up these five trends, one can envision a global oil crunch at the horizon — – most probably within the present decade. Unfortunately, however, the general public will not heed such a rational vision. And, even if it did, it would be loath to respond to the implied threat. In its defence, it should be said that many actors are constantly and consistently reassuring it: the press (even parts of the specialised press), most politicians, some international institutions, a couple of major oil companies and naturally OPEC. But this can only last until petrol stations post ‘empty’, natural gas supplies are suddenly shunted and, eventually, the lights go off.
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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 | 0.001 | 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 | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".