The Carbon Footprint of an East African Forestry Enterprise
Bibliographic record
Abstract
Green Resources AS, a plantation, carbon offset, forest products, and renewable energy company with operations in Eastern Africa, calculated carbon footprints for 2008 and 2009. In both years, the footprint was dominated by removals of CO2 from the atmosphere attributable to afforestation. These removals were more than 17 times the emissions from the company’s value chain. The largest difference between the 2008 and 2009 footprints was due to loss of forest carbon caused by fire. Otherwise, the most important changes in the footprint were related to plantation expansion and growth, and increased output of products in 2009, which caused increases in several types of emissions. The remaining elements of the footprint (manufacturing, forestry operations, transport, and upstream emissions related to non-fibrous inputs, fuels, and electricity) were approximately equal. The use of the charcoal manufactured by the company avoided coal-related emissions equal to approximately one-quarter of the company’s value chain emissions.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".