Bibliographic record
Abstract
A quick overview of major recent developments in the Canadian airport scene includes looks at Toronto/Pearson, which has a new Terminal 1, which the author describes as an exercise in architectural grandeur. Opened for operations in April 2004, its style evokes Victorian railway stations, with sweeping curves and high ceilings. It is a larger version of Terminal 3, which opened in 1991. A pier structure extending from the departure hall toward Runway 15L/33R is designed to give the maximum surface contact for aircraft. White-painted girders attached to wishbone-shaped supports allow the roof load to be supported past long windows. The front curb seems small, considering that 24.7 million passengers pass through it in a typical year, but there are three levels, rather than the traditional two. Private lanes serve commercial traffic, which improves capacity. Passengers are segregated from cars and are guided by information screens that can be changed to provide different terminal info as needed. There are some 450 different displays, 50 express-use kiosks for all providers and 300 electronic message boards. Anticipating the new Airbus A380, there are two feeds on one carousel to move luggage more quickly. An automated people mover is set to start operation in early 2006 to move people from Terminal 1 to Terminal 3 and the planned new remote discount parking lot. The people mover will also hook up with a proposed air rail terminus to be built by the federal government and link it to Toronto's downtown Union Station.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.438 | 0.156 |
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".