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The Effects of Geometry on the P-Wave Seismic Response of Massive Mineral Deposits

2017· book-chapter· en· W3024854244 on OpenAlex
Kebabonye Laletsang, Charles A. Hurich

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

VenueAdvances in geospatial technologies book series · 2017
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsGeologyStack (abstract data type)DiffractionAmplitudeConcentricGeometrySeismologySeismic attributeGeophysical imagingSeismic wavePhysicsOpticsComputer scienceMathematics

Abstract

fetched live from OpenAlex

Results from analogue seismic modelling aimed to investigate the effect that the geometry of a mineral deposit imposes on its seismic response are presented. 3D Seismic data were acquired on two physical models representing the possible end-member geometries of mineral deposits. The physical modelling involved acquisition of 3D pre-stack data on scale models. The results for the ellipsoidal model comprised closed, continuous, circular diffraction patterns in time slices. For the cylindrical model, the quality of the stack was degraded by the scattering caused by the rugged surface. The diffraction patterns were discontinuous and comprised the diagnostic concentric, circular amplitude peaks and troughs which would allow identification of drill targets in field data. The results show that 3D seismic data are valuable in mineral exploration because they provide (1) enhanced spatial resolution, and (2) slices of time help to identify the seismic response of small seismic targets with complex geometry.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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