MétaCan
Menu
Back to cohort
Record W3026927079 · doi:10.1080/23744731.2020.1771808

Normal and extreme aircraft accelerations and the effects on exposure to expiratory airborne contaminant inside commercial aircraft cabins

2020· article· en· W3026927079 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

VenueScience and Technology for the Built Environment · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsClimbDescent (aeronautics)Context (archaeology)AeronauticsEnvironmental scienceAerospace engineeringMeteorologyEngineeringGeologyPhysics

Abstract

fetched live from OpenAlex

A novel dataset based on satellite observations of aircraft positions was utilized to estimate normal accelerations of commercial aircraft during climb and descent legs. Further, these accelerations are used to simulate the effects on exposure to expiratory airborne contaminant inside commercial aircraft cabins. Compared to previous studies, which reported exposures more than twice due to high aircraft accelerations during the climb leg, the new findings suggest lower aircraft accelerations that result in exposures on par with steady level flights during climb and descent legs. The new findings place previous studies in context to be interpreted as extreme conditions only while they call for more detailed experimental investigations.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
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 studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.216
Teacher spread0.200 · 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