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Record W2006362183 · doi:10.1190/1.3064156

Table of elastic constants for isotropic media

2009· article· en· W2006362183 on OpenAlexaff
Jesper M Smidt

Bibliographic record

VenueThe Leading Edge · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsTable (database)IsotropyPhysicsComputer scienceOpticsDatabase

Abstract

fetched live from OpenAlex

Various reference volumes and seismological textbooks have tables of elastic constants for isotropic media expressed in terms of each other in order to present a quick, authoritative reference for translation of elastic constants from one set of parameters to another. As an example, one may possess seismic inversion results in terms of acoustic impedance, compressional-to-shear velocity ratio and density, yet prefer to interpret them in terms of the Lamé impedances, λρ (lambda-rho) and μρ (mu-rho), and possibly also λ/μ, the Lamé impedance ratio, as championed by Goodway (2001). The table presented here is developed from the tables of Sheriff (1991), and Mavko et al. (1998), with added material from Goodway (2001) and Helbig (1994). Its merit is to be more comprehensive than previous tables known to the author, but it also comes with a certain redundancy. Though there is a good probability that the reader may find the desired “translation” here, no such table will be complete, let alone perfect.

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)0.005
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: Dataset · Consensus signal: none
Teacher disagreement score0.130
Threshold uncertainty score0.435

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0010.000
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1300.081

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 head0.024
GPT teacher head0.239
Teacher spread0.215 · 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
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

Citations5
Published2009
Admission routes1
Has abstractyes

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Same venueThe Leading EdgeSame topicSeismic Imaging and Inversion TechniquesFrench-language works237,207