Bibliographic record
Abstract
He has been on the faculty of the Banff Centre for the Arts Wired Writing Studio, and contributed to the mentorship program of the Writers' Federation of Nova Scotia.His interests include the natural sciences, religion, mythology, and the visual arts.Some of his artwork has appeared in galleries in Halifax and Seoul, South Korea.He collected fossils for fourteen years.During this time he found a neural arch of a 350-million-year-old (Carboniferous) amphibian previously thought to have gone extinct in the Devonian period.His interest in religion has included visits to churches and cathedrals in France, Ireland, and Argentina, mosques in Istanbul, Rumi's tomb in Konya, and Buddhist temples and monasteries in China.One of his interests in the last few years has been meteorites, his collection including a meteorite from Nantan, China, that fell in 1516.Another of his pastimes is collecting Stone Age tools, such as an 80,000-year-old Neanderthal digging tool made from the jawbone of a cave bear found in Germany.All of these pursuits help to ground his work and fuel his imagination.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.241 | 0.140 |
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".