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Record W2899686404 · doi:10.1016/j.crme.2018.10.001

A model for the aerodynamic coefficients of rock-like debris

2018· article· fr· W2899686404 on OpenAlex
Vincent Chai, Dushyant Parkhi, Sethu Raman Boopathy, Junting Xiang, Jörg Schlüter

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueComptes Rendus Mécanique · 2018
Typearticle
Languagefr
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersDefence Science and Technology Agency - SingaporePetroleum Technology Research Centre
KeywordsAerodynamicsDebrisWind tunnelAerodynamic forceGeotechnical engineeringObject (grammar)GeologyMagnitude (astronomy)Aerospace engineeringMarine engineeringStructural engineeringEngineeringComputer scienceEnvironmental scienceArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

This study presents a model to determine the aerodynamic forces on an irregularly shaped object for prediction of trajectories of debris. We classify the debris according to shape and use wind tunnel tests to create a database of aerodynamic forces of similarly sized objects. We have then validated the database results against wind tunnel measurements of aerodynamic coefficients of rock-like debris objects. Although the individual errors may be significant, the results show a generally good agreement with our model prediction and a small average error.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.743
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.252
Teacher spread0.232 · 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