Bibliographic record
Abstract
‘Are you going to go there just to see a church?’ ‘I have to start somewhere, that’s one of the addresses in the arrest warrant at the very least!’ A friend of mine in Toronto was genuinely questioning the rationale of that trip. But … I have to see the places, I need to see the spaces. It was April 2017 and I was staying in Toronto. It took me pretty much two hours to travel to the site of the church on public transport; I hadn’t rented a car. I wish I had. I wouldn’t have had parking issues anyway, as in front of the St Clare of Assisi Catholic Church, on 150 St Francis Avenue, in Woodbridge, a large suburban community in the city of Vaughan, just north of Toronto, there is no scarcity of parking space. It was windy, just a few days earlier it had snowed in Montreal, and Toronto was ice cold, or at least it was for me, in April … one should feel spring, right? Right. Anyway, I had bought a new pair of snow boots, insulated and furry inside, so I was ready to face what to me was definitely still winter.
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 | 0.000 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".