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Record W2504960715 · doi:10.1190/1.9781560801719.ch5

5. Inversion for Applied Geophysics: A Tutorial

2005· book-chapter· en· W2504960715 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.

Bibliographic record

VenueSociety of Exploration Geophysicists eBooks · 2005
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Introduction Throughout this book there are numerous cases where geophysics has been used to help solve practical environmental, geotechnical, and exploration problems. The typical scenario is first to identify the physical property that is diagnostic of the sought geologic structure or buried object, for example, density, seismic velocity, electrical conductivity, or magnetic susceptibility. The appropriate geophysical survey is then designed and field data are acquired and plotted. In some cases the information needed to solve the problem may be obtained directly from these plots, but in most cases more information about the subsurface is required. As an example, consider the magnetic field anomaly map presented in Figure 2. The existence of a buried object, and also approximate horizontal locations, can be inferred directly from that image. The map, however, presents no information about the depth of the object or details regarding its shape. To obtain that information the data need to be inverted to generate a 3D subsurface distribution of the magnetic material.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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 head0.034
GPT teacher head0.234
Teacher spread0.201 · 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