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Record W1979302698 · doi:10.1190/1.3054783

Field data comparison: 3C‐2D data acquisition with geophones and accelerometers

2008· article· en· W1979302698 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeophysics and Sensor Technology
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsGeophoneAccelerometerData acquisitionGeologyRemote sensingComputer scienceVertical seismic profileEngineeringSeismologyOperating system

Abstract

fetched live from OpenAlex

We report on a field comparison of different seismic motion sensors. The CREWES Project at the University of Calgary acquired a 3C‐2D seismic line in the Spring Coulee area of Southern Alberta in January 2008. This was a unique opportunity to compare two types of multicomponent sensors with acquisition occurring at the same time and with the same receiver parameters. This 6.52 km 2D acquisition was laid out with a digital MEMS accelerometer: the DSU3‐428 and the accompanying Sercel 428XL recording system; as well as an analog 3C geophone: the SM‐7 high resolution geophone element placed in a modified PE‐6/S nail type case co‐developed by Sensor Nederland (A Division of ION Geophysical) and ARAM Systems with the accompanying ARAM Aries MC recording system. There have been limited acquisition comparison tests performed and/or published with MEMS accelerometers and analog geophones in the past; the purpose of this study is to compare data acquired with single‐point 3C receivers laid out side‐side in a commercial recording environment.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.320

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 head0.062
GPT teacher head0.242
Teacher spread0.180 · 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

Quick stats

Citations4
Published2008
Admission routes3
Has abstractyes

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