Bibliographic record
Abstract
As I was thinking about Dr. Alan Drengson and his legacy, contemplating what I could write about him that would capture his essence, I looked down at a card that was sitting on the table beside me and everything became clear.The card is produced by the Ecoforestry Institute Society.The photograph on the front (Image 1) -taken at Wildwood Ecoforest on Vancouver Island by EIS Board member, writer, and photographer Hans Tammemagi -is of a big, old stump in front of a rustic wooden shed with upright boards as siding and a small wood-framed window.The edges of the stump where the tree had been cut show that it had continued to grow after that, forming the beginnings of a so-called "sealed stump."Emerging from the rotting centre of the stump is a large red huckleberry bush and a little clump of salal with its oval, evergreen leaves.Light green lichens encrust the outer bark of the stump and there is more salal growing on the ground around it.A forest of big and medium sized Douglas-firs and some smaller deciduous trees emerge in the background behind the shed.
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 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.043 | 0.020 |
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".