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Record W2018785903 · doi:10.1680/tran.13.00081

New Quito airport, Ecuador: high-flying success via collaboration

2015· article· en· W2018785903 on OpenAlexaboutno aff
Chris Chalk, David Beare

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Transport · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsInternational airportDestinationsScope (computer science)BusinessBusiness travelGovernment (linguistics)Latin AmericansFinanceTourismGeographyTransport engineeringPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Set at 8500 ft (2590 m) high in the Ecuadorian Andes the New Quito International Airport, opened in February 2013, is a landmark both in airport development in Latin America as well as in project finance. The location of this airport, which replaced the old airport that had become absorbed within the City of Quito surrounded by active volcanoes, added a number of unique challenges. As well as handling over 5 million passengers annually, the airport also exports some 20 million roses per day during peak times to destinations around the world. This paper summarises the project scope and benefits, key responsibilities, technical challenges and collaborative working that enabled the US$700 million airport development to meet contractual deadlines. Set up as a government-to-government Canadian–Ecuadorian prime contract, drawing in investors from Canada, USA and Brazil, with international financial institutions from the USA and Canada, the airport was built to international standards with suppliers from across the Americas and Europe, within the exacting obligations of the International Financial Organisation's Equator principles. The paper also examines the total concession structure including impact of a political event and the use of multiple sub-concessions needed for a fully operational airport. The authors' involvement throughout the planning, design and development of the new airport brings together important reference material for the particular benefit of those involved in transport concession projects.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.021
GPT teacher head0.209
Teacher spread0.188 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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