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Record W643541987

Automated Access: The Recently Completed Automated People Mover at Toronto Pearson International Airport

2006· article· en· W643541987 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCivil engineering · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownTrainInternational airportTransport engineeringTelecommunicationsEngineeringAeronauticsGeography
DOInot available

Abstract

fetched live from OpenAlex

In this article, the author discusses the Greater Toronto Airports Authority's (GTAA) construction of an automated people mover (APM) at Toronto Pearson International Airport, Canada's busiest airport, which served 29.9 million passengers in 2005. This project is part of the GTAA's larger Terminal Development Project which is designed to completely renovate two of the airport's three terminals. The article describes the design and construction of three APM stations and the dual elevated guideways which follow an alignment that is adjacent to the roadways leading to the arrivals and departures level serving Terminals 1 and 3. Two independent cable systems operate the APM system in dual shuttle mode. The trains consist of six vehicles, each of which can accommodate 25 passengers. The $136 million project began operation in July 2006. Potential future expansion plans would allow for increasing the system to a total length of 1800m, the addition of a fourth station, and a connection to the Air Rail Link enabling airport access from 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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.204
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it