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Record W3012611513 · doi:10.1016/j.rineng.2020.100114

Visualization of acoustically-assisted fluid flow in unconsolidated confined porous media

2020· article· en· W3012611513 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueResults in Engineering · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsPorous mediumMaterials sciencePorosityNanofluidWork (physics)Flow (mathematics)Petroleum engineeringGeotechnical engineeringAcousticsGeologyMechanicsComposite materialNanoparticleNanotechnologyEngineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Acoustic techniques can deliver a high-power output in a short range, hence the application of acoustic excitation in conjunction with well stimulation and in-situ recovery methods may facilitate hydrocarbon production. In this work, an experimental apparatus is designed to directly vibrate pore fluids and visualize miscible- and immiscible-flood displacements in unconsolidated, confined porous media. A miscible-flood experiment is provided as an example, where iron oxide nanofluid is injected through a water-saturated sandpack, under both sonicated and silent conditions, to investigate how mechanical excitation influences the transport and retention of nanoparticles in porous media.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.234
Teacher spread0.217 · 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