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Record W2792459327 · doi:10.1115/1.2016-mar-2

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2016· article· en· W2792459327 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.

Bibliographic record

VenueMechanical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsSupersonic speedSonic boomJet engineAerospace engineeringMach numberAeronauticsEngineeringBoomService (business)Jet (fluid)Business

Abstract

fetched live from OpenAlex

This article explores efforts that are being put into developing a business jet called AS2 and various challenges in developing the same. Aerion’s 12-seat tri-engine AS2, unveiled in spring 2014, is designed to have a range up to 5000 nautical miles; reach 51,000 feet; and cruise at speeds between Mach 1.2 and Mach 1.6. About the time it is ready to fly commercially, possibly as early as 2023, the market could support annual sales of 30 supersonic business jets. NASA and Lockheed Martin have been exploring a variety of options for quieting sonic booms. In its Strategic Implementation Plan, released in 2015, NASA states that ‘the viability of commercial supersonic service depends on permissible supersonic flight over land.’ It is however noted that the success of the next generation of supersonic transport will ultimately come down to economics. Prospective buyers of supersonic business jets will include corporations and ultra-high net worth individuals.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.989
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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.178
Teacher spread0.171 · 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