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Record W2143105265 · doi:10.1287/inte.2013.0683

Mathematical Programming Guides Air-Ambulance Routing at Ornge

2013· article· en· W2143105265 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueINFORMS Journal on Applied Analytics · 2013
Typearticle
Languageen
FieldEngineering
TopicVehicle Routing Optimization Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOperations researchWork (physics)Computer scienceFixed wingRouting (electronic design automation)Route planningAir traffic controlRange (aeronautics)Vehicle routing problemOperations managementAeronauticsTransport engineeringEngineeringComputer networkWing

Abstract

fetched live from OpenAlex

Ornge provides air-ambulance services to the province of Ontario. A major part of its services involves prescheduled transports between medical facilities. These transports almost exclusively require fixed-wing aircraft because of the distances involved and cost considerations. The requests are received in advance, scheduled overnight, and typically executed the following day. We describe our work in developing a planning tool that determines an assignment of requests to aircraft to minimize cost, subject to a range of complicating constraints. Ornge flight planners use the tool daily, resulting in substantial savings over the manual approach they used previously to develop schedules. We describe the problem, our formulation, its implementation, and the impact on operations at Ornge.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.019
GPT teacher head0.258
Teacher spread0.240 · 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