Bibliographic record
Abstract
Devon Canada Corporation is a wholly-owned subsidiary of U.S. based Devon Energy Corporation (www.devonenergy.com). Devon Canada has participated in the Voluntary Challenge (now the CSA GHG Registry) on Climate Change since 1995. As part of our participation, we have submitted action plans and progress reports on a regular basis. Devon Canada’s 2004/2005 Annual Progress Report and Action Plan for submission to the CSA Canadian GHG Challenge Registry is contained herein and includes an inventory of greenhouse gas (GHG) emissions and energy usage for 2004 and reduction initiatives for 2004 and 2005. Devon Canada has continued to improve its data gathering and reporting in each reporting year. Operated production steadily increased during most of the 1990’s but has levelled off and slightly declined since our baseline year of 2001 due to declining reservoirs and divestitures of non-core properties in the Western Canadian Sedimentary Basin (WCSB), our primary base of operations. Devon Canada has expended significant effort toward our goal of GHG emission reduction. Through the implementation of hundreds of individual emission reduction projects over the
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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.292 | 0.098 |
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".