Bibliographic record
Abstract
The Oil and Natural Gas Corp, Ltd. (ONGC), headquartered in Dehradun, India, has joined seven U.S. and Canadian oil and natural gas companies as a partner in a U.S. Environmental Protection Agency program to reduce greenhouse gas emissions. EPA's Natural Gas STAR International Program aims to reduce methane emissions from the oil and natural gas sector while delivering more gas to markets around the world. With this partnership, ONGC agrees to implement emissions reduction practices and to submit annual reports on progress achieved; EPA agrees to assist ONGC with training technicians in new cost‐effective technologies that will help achieve target emissions. The Natural Gas STAR International Program is administered under the Methane to Markets Partnership, a group of 20 countries and 600 companies across the globe that since 2004 has volunteered to cut methane emissions. More information on EPA's agreement with ONGC can be found at http://www.epa.gov/gasstar/index.htm; information about the Methane to Markets Partnership can be found at http://www.methanetomarkets.org.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".