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Record W7099102634

Measuring the Head Tilt Illusion During Sustained Acceleration Canadian Approach to

2012· article· en· W7099102634 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReliability and Maintenance Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsTilt (camera)AviationAviation accidentAccelerationHead (geology)IllusionSpatial disorientation
DOInot available

Abstract

fetched live from OpenAlex

In the early days of aviation, the vast majority of accidents were the result of mechanical failure. As aviation matured and the technology improved, more and more mishaps could be assigned to a problem in the human end of the equation. At present, these human problems, or human factors, make up the majority of causes of aircraft mishaps. One of the principal human factors that are causal in mishaps is spatial disorientation (SD). As shown in Figure 1 (see Page 2), which is drawn from USAF Safety Center data, the rate of USAF SD related mishaps per 100,000 flying hours changed little from 1991 to 2000. Study of the 20 years prior to this time reveals similar numbers.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.802

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)0.0000.000

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 head0.021
GPT teacher head0.196
Teacher spread0.176 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations0
Published2012
Admission routes1
Has abstractyes

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