Bibliographic record
Abstract
The PCOR Partnership is off to a very exciting and ambitious start. Task 1 activities have included the planning and execution of an internal kickoff meeting, participation in the DOE's national kickoff meeting, and the planning and execution of the first meeting of the PCOR Partnership at the Energy & Environmental Research Center (EERC). Task 2 activities have focused on developing effective and critical partnerships. A plan has been developed to utilize Dakota Gasification Company's (DGC) experience and data with respect to their participation in the enhanced oil recovery project at Weyburn, Saskatchewan. A solid line of communication has been developed with the Interstate Oil & Gas Compact Commission (IOGCC) for the mutual benefit of the PCOR Partnership and IOGCC's compensatory efforts. Task 3 activities have been focused on developing a foundation of background materials in order to avoid a duplication of efforts and provide the best outreach and educational materials possible. Progress in Task 4, Characterization and Evaluation, has included the development of a database format, the preliminary collection of data regarding CO{sub 2} sources and sinks, and data on the performance and costs for CO{sub 2} separation, capture, and treatment to prepare the fluid for pipeline transportation. Task 5 activities have resulted in a conceptual model for screening and qualitatively assessing sequestration options. Task 5 activities have also been useful in structuring data collection and other activities in Tasks 2, 3, and 5.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.096 | 0.026 |
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".