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Record W1987384619 · doi:10.2466/pms.98.3c.1219-1224

Geophysical Variables and Behavior: C. Increased Geomagnetic Activity on Days of Commercial Air Crashes Attributed to Computer or Pilot Error but Not Mechanical Failure

2004· article· en· W1987384619 on OpenAlexaff
Neil M. Fournier, Michael A. Persinger

Bibliographic record

VenuePerceptual and Motor Skills · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectromagnetic Fields and Biological Effects
Canadian institutionsLaurentian University
Fundersnot available
KeywordsEarth's magnetic fieldCrashPoison controlVariance (accounting)Environmental scienceMedicineComputer sciencePhysicsMedical emergencyMagnetic field

Abstract

fetched live from OpenAlex

Global geomagnetic activity (aa values) for the days of crashes of airplanes and for each of the three days before and after the crashes were compared for 373 events (years 1940 through 2002) attributed to unknown factors, mechanical errors, electronic/computer failures or pilot errors. Interactions between days and classifications of the crashes were due to the significantly greater geomagnetic activity on the days of crashes attributed to pilot or computer error but not to mechanical or unknown factors. Successive temporal analyses indicated that the elevated activity on the days of crashes attributed to pilot error have not changed over time, but there was an increase in those attributed to electronic errors after 1965. No more than 9% of the variance in geomagnetic activity on the days of the crashes was associated with the type of crash. These results are consistent with our hypothesis that some factor or factors associated with relative increases in geomagnetic activity may affect complex electronic systems composed of either silica (computer) or carbon (brain) aggregates.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.728

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 head0.013
GPT teacher head0.245
Teacher spread0.233 · 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 designBench or experimental
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

Citations1
Published2004
Admission routes1
Has abstractyes

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