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Record W2041613712 · doi:10.1029/2008eo400001

Capturing the Acoustic Fingerprint of Stratospheric Ash Injection

2008· article· en· W2041613712 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

VenueEos · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsVolcanic ashCruiseEnvironmental scienceTropopauseVolcanoStratosphereLatency (audio)Vulcanian eruptionGeologyMeteorologyRemote sensingSeismologyComputer scienceTelecommunicationsAtmospheric sciencesGeography

Abstract

fetched live from OpenAlex

More than 100 separate incidents of interactions between aircraft and volcanic ash were documented between 1973 and 2003. Incidents on international flight paths over remote areas have resulted in engine failures and significant damage and expense to commercial airlines. To protect aircraft from volcanic ash, pilots need rapid and reliable notification of ash‐ generating events. A global infrasound array network, consisting of the International Monitoring System (IMS) and other national networks, has demonstrated a capability for remote detection of Vulcanian to Plinian eruptions that can inject ash into commercial aircraft cruise altitudes (approximately 12 kilometers) near the tropopause. The identification of recurring sound signatures associated with high‐ altitude ash injection implies that acoustic remote sensing can improve the reliability and reduce the latency of these notifications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.553

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)0.0010.000

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 head0.008
GPT teacher head0.200
Teacher spread0.192 · 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