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Record W4243100277 · doi:10.1190/tle34050572.1

Reviews

2015· article· en· W4243100277 on OpenAlexaff
David P. Bartel, Andreas Rüger, Wooil M. Moon, William R. Green

Bibliographic record

VenueThe Leading Edge · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsCollege of Veterinarians of British ColumbiaResearch Manitoba
Fundersnot available
KeywordsMicroseismHydraulic fracturingGeologyPhilosophyEngineering physicsArt historyEngineeringArtPetroleum engineeringSeismology

Abstract

fetched live from OpenAlex

Microseismic Imaging of Hydraulic Fracturing: Improved Engineering of Unconventional Shale Reservoirs, by Shawn Maxwell, ISBN 978-1-56080-315-7, 2014, SEG Distinguished Instructor Series No. 17, US $58 (US $45 member price). Practical and Applied Hydrogeology, by Zekâi Sen, ISBN 978-0-12-800075-5, Elsevier, 2014, 424 p., US $110.50 (eBook available). Seismic Reflections of Rock Properties, by J. Dvorkin, M. A. Gutierrez, and D. Grana, ISBN 978-0-521-89919-2, 2014, Cambridge University Press, 324 p., US $75 (eBook available). The Computing Universe: A Journey through a Revolution, by Tony Hey and Gyuri Papay, 2014, ISBN 978-0-521-15018-7, Cambridge University Press, New York, 397 p., US $39.99.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.467
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0030.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.4670.394

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 head0.086
GPT teacher head0.274
Teacher spread0.189 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2015
Admission routes1
Has abstractyes

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