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Viability assessment of integrated P- and S-wave surveys using ultrasound

2022· article· en· W4283763904 on OpenAlexaff
Bilal Hassan

Bibliographic record

VenueEarth sciences and subsoil use · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsContext (archaeology)Ultrasonic sensorGeologyPhase (matter)Displacement (psychology)AmplitudeFlow (mathematics)Artifact (error)MechanicsComputer scienceAcousticsPhysicsOptics

Abstract

fetched live from OpenAlex

Potential of, integrated geophysical, especially P- and S-wave combined near surface surveys, is assessed; demonstrated with use of sparingly, reduced chronographic i. e., time and velocity, (1 MHz) ultrasonic imaged data. Case of aqueous and non-aqueous, predominantly, fossil fuel origins spills seepage within near-surface geology is examined in terms of evaluation of possible complexities of fluids and surrounding interactions; which are experimentally simulated embodied as flow components of an immiscible displacement process. Such processes are understood and studied widely, within various, especially near-field geo- and engineering including environmental and also geo-disaster contexts. Interesting relevant scenarios, including aspects, of geological complexity of well known geographical locations while their subjugation also to various, whether natural or anthropogenic, stressors are presented alongside pertinent theory for better grasp, including plausibility, of methodology and inferring. Experimental analogues and geometrical constraints are explained in detail. Ultrasonic P- and S-wave, data in relevant context, also verified analytically, are comprehensively evaluated. S-wave data not only corroborates P-wave data attributes in time-space localization of displaced, from displacing phase, including a “dim spot”, an interesting artifact corresponding to interface (or mixed phase) region, S-wave also manifested other elastic and thermo-mechanical characteristics of the same feature. Further a flow rate, especially, that of injection, control or dependence of a planned displacement process was confirmed, for example if required in tracer and remedial studies. S-waves characteristic suitability to reveal other fluid-fluid and fluid-solid interaction peculiarities at micro and possibly at nano scale, as amplitude effects, is foreseen to assume significant promise.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.260
Teacher spread0.209 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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