MétaCan
Menu
Back to cohort
Record W2183870792

Borehole Geophone Repeatability Experiment

2011· article· en· W2183870792 on OpenAlexaffabout
Peter Gagliardi, Don C. Lawton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeophoneRepeatabilityGeodesyGeologyBoreholeRotation (mathematics)SeismologyMathematicsStatisticsGeotechnical engineeringGeometry
DOInot available

Abstract

fetched live from OpenAlex

Summary Time-lapse vertical seismic profile data was obtained near Violet Grove, Alberta, using an array of eight 3component geophones at depths between 1497 m to 1640 m. Baseline data were recorded in 2005 and the monitor recorded in 2007. Analysis of rotation angles was undertaken for both surveys, resulting in differences of less than 2° for 54.2% in Line 2 and 85.9% in Line 3. Rotation angles were found to be more consistent at offsets greater than about 500 m. NRMS analysis gave averages of 61.4% and 45.3% for horizontal components, and 42.8% and 41.4% for the vertical component. Predictability analysis showed averages of 0.72 and 0.83 for horizontal components and 0.83 and 0.86 for the vertical component. In addition, traces were examined visually, and showed good qualitative repeatability. Since the receivers were cemented into place, the greatest effect on the repeatability was judged to be from differences in noise and small differences between the source locations between surveys.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.033
GPT teacher head0.203
Teacher spread0.170 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2011
Admission routes2
Has abstractyes

Explore more

Same topicSeismic Waves and AnalysisFrench-language works237,207