Bibliographic record
Abstract
Aboriginal people, Australia forest fire-burning practices 82 access rights 43, 59, 65, 235 accountability, goal-setting, resultspublication 243 accounting practices, specified activities for 153-4, 203 accreditation of verification bodies 261 advertising and consumer outreach in Europe for FSC timber 290-91 African Timber Organization, Libreville, Gabon, 1993 89 agroforestry mix of livestock, crops, with woody perennial 158 airborne pollution impact 108 Amazon River basin tripling of existing protected reserves 186 aquatic habitats maintenance, forest assistance 233 Asia, per capita, consumption of wood products, increase 6 aspirational statements, non-legally binding, on forests 131 assurance mechanism timber products from managed stocks, verification 292 audit assessment, annual, Forest Stewardship Council 281 Australia, non-binding codes of conduct 20-21 'avoided deforestation' 162 Brazil, compensation requirement 172 and carbon market 170-71 issues raised by 169 Baltic states, emission control 138 'California effect', 'race to the top' 265-6 Canadian Standards Association 270
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.693 | 0.462 |
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".