Verification of the Danish 1990, 2000 and 2010 emission inventory data
Bibliographic record
Abstract
Danish emission values, implied emission factors and activity data for the national greenhouse gas inventory are assessed according to an updated verification procedure. Focus is on 25 identified key categories, represented by 29 verification categories, and 28 Annex II indicators covering energy, agriculture, industry and waste. The data are based on the national greenhouse gas inventories for the years 1990 (base year), 2000 and 2010, as reported in 2012, and provided by the UNFCCC and EU. Inter-country comparison and time series consistency check of emissions and implied emission factors is made for EU15 countries, excluding Luxemburg and including Norway and Switzerland and for some verification steps also including Australia, Canada, Japan, Russian Federation, USA and aggregated values for EU15 and EU27. National and inter-country verification and time trend consistency check of activity data is made with data for energy consumption (Eurostat), agricultural statistics (Eurostat), industrial processes (UN) and waste disposal (OECD). Verification in this approach is a combination of qualitative and quantitative assessments and can assist to identify sectors and categories that require more attention and thus facilitates the prioritisation of efforts that are required to obtain more accurate and reliable emission inventories in the future.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".