MétaCan
Menu
Back to cohort
Record W2074963514 · doi:10.1029/2006eo100001

U.S. warning system detected the Sumatra Tsunami

2006· article· en· W2074963514 on OpenAlexaff
Jim Gower, F. I. González

Bibliographic record

VenueEos · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsBuoyPacific oceanGeologyWarning systemSeismologyOcean bottomTsunami waveOceanographyIndian oceanGeographyMeteorologyTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Although the December 2004 great Sumatra earthquake and the resulting tsunami were very distant from the northeast Pacific Ocean, the U.S. Deep‐ocean Assessment and Reporting of Tsunamis (DART) array in the northeast Pacific successfully demonstrated high sensitivity and provides useful data for understanding the propagation of the tsunami. At the time of the tsunami, the Pacific DART network already was one of the most sophisticated tsunami detection systems in operation.The network, which then consisted of eight stations (seven U.S. and one Chilean), now consists of 11 stations (10 U.S. and one Chilean) [ González et al ., 2005] (Figure l). Each station is equipped with a bottom pressure recorder (BPR) transmitting data acoustically from the ocean bottom to a surface buoy, which then passes the data to tsunami warning centers and other land stations by satellite communication links.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
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)0.0000.001

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 head0.011
GPT teacher head0.204
Teacher spread0.193 · 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.

Study designObservational
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

Citations4
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueEosSame topicUnderwater Acoustics ResearchFrench-language works237,207