Bibliographic record
Abstract
According to the International Energy Agency (IEA), global demand for energy will grow by more than half over the next quarter-century, exceeding 325 million barrels of oil equivalent per day. It is estimated that oil and gas will count for close to 60% of the total energy supply. In order to meet this challenge, massive investments are required in a number of fronts from exploration and production, to refining and transportation. Additionally, regional and global political and economic issues will play a key role in our success to deliver energy for the world. However, the most important and needed resource to achieve such an ambitious goal is the human factor, the people. Increasing demand for energy worldwide will result in an increasingly important role for geoscientists. In other words, efforts to meet the global demand for energy have put an onus on geoscientists to succeed. So the real question is how do we, the geoscientists, succeed?
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.161 | 0.160 |
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".