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Record W4393663521 · doi:10.5281/zenodo.5603835

Microseismic source parameters from induced seismicity in the Horn river basin (British Columbia) [Dataset]

2021· dataset· en· W4393663521 on OpenAlexaboutno aff
Adam Klinger, Maximilian J. Werner

Bibliographic record

VenueExplore Bristol Research · 2021
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
FundersResearch Councils UK
KeywordsMicroseismInduced seismicitySeismologyGeologyFrench hornStructural basinGeomorphology

Abstract

fetched live from OpenAlex

This is a database of results linked to the associated manuscript (Klinger and Werner, 2021) which has been submitted to Geophysical Journal International and is currently in review. We report magnitudes, corner frequencies and stress drops of microseismic events linked to fault reactivation during hydro-fracturing operations in the Horn river basin (British Columbia), as well as the corresponding uncertainties for these parameters. Stress drops are calculated using a Brune model (Brune, 1970) and uncertainties are calculated using a bootstrapping technique. Prior to publication please cite this database using the following two references: Klinger, A.G., Werner, M.J. (2021). Stress drops of hydraulic fracturing induced microseismicity in the Horn River basin: Challenges at high frequencies recorded by borehole geophones. <em>Manuscript submitted to Geophysical Journal International . </em> Klinger, A.G., Werner, M.J. (2021). Microseismic source parameters from induced seismicity in the Horn river basin (British Columbia) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5603835.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.817
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0030.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.098
GPT teacher head0.311
Teacher spread0.212 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2021
Admission routes1
Has abstractyes

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