Bibliographic record
Abstract
If it weren’t for the cement pipe segments nearly nine feet in diameter, oversize yellow backhoes, towering piles of sand, and yawning trenches scattering the streets, the section of Toronto near the junction of Connaught and Fargo avenues would look like an ordinary residential neighborhood. In spring 2011 this area of comfortable-looking contemporary houses surrounded by tidy landscaping was a construction zone as its storm sewers, most fewer than 20 years old, were ripped up and replaced with much larger pipes. The purpose of all the disruption? To prevent the flooding of basements and garages that has plagued these homes during unexpectedly heavy rains in recent years. into a densely developed city like Toronto is technically challenging and expensive—especially considering that the old pipes were still well within their useful life spans. “We’re rebuilding systems in an area of the city that, all things being equal, we shouldn’t have had to worry about for several decades to come,” he says. But extreme weather calls for extreme plans. City officials deemed the new standard necessary after two huge soakers, one in May 2000 and an even bigger one in August 2005, lit up the city’s switchboards with thousands of complaints of flooding and raw sewage backing up into basements. In fact, no fewer than
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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; both teacher heads agree on what is shown here.
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".