Bibliographic record
Abstract
The Interstate Oil and Gas Compact Commission (IOGCC) engaged in numerous projects outlined under the scope of work discussed in the United States Department of Energy (DOE) grant number DE-FG26-01BC15336 awarded to the IOGCC. Numerous projects were completed that were extremely valuable to state oil and gas agencies as a result of work performed utilizing resources provided by the grant. There are numerous areas in which state agencies still need assistance. This additional assistance will need to be addressed under another grant because funding resources have been exhausted under The scope of work objectives for the eight projects covered under this grant is as follows: (1) Improve uniformity within state oil and gas data management efforts. (2) Conduct environmental compliance workshops and related educational projects on natural gas and oil exploration and production. (3) Improve regulatory efficiency through partnering opportunities provided by the Appalachian Illinois Basin Directors. (4) Promote the development and implementation of risk-based environmental regulation at the state level through an expertise-sharing program that brings stakeholders together to develop guidelines and models to meet regulatory challenges. (5) Support the IOGCC's regulatory streamlining efforts, including the identification and elimination of unnecessary duplications of effort between state and federal programs dealing with exploration and production on public lands, and identify the need to enhance and regionalize regulatory coordination and cooperation among the states. (6) Involve states and provinces of Canada that have offshore petroleum exploration and production in a regulatory sharing alliance to identify areas of concern that may be incorporated into standard practices for offshore environmental and regulatory compliance. (7) Coordinate efforts with the U.S. Environmental Protection Agency (EPA) to ensure that adequate information is available to the public regarding oil and gas exploration and production operations consistent with the intent of ''community right-to-know'' programs. (8) Demonstrate leadership in educating the public about the exploration, extraction and refining of petroleum; the economic value of domestic petroleum and its byproducts; conservation measures and their benefits; and other topics designed to assist the American public in gaining understanding of the importance of domestic resources and defining a true picture of those resources.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.621 | 0.491 |
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".