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Record W1520356769

Laboratory assessment of vibration emissions from vibrating forks used in simulated beach cleaning

2011· article· en· W1520356769 on OpenAlexvenueno aff
Thomas W. McDowell, Xinsheng Xü, Christopher Warren, Daniel E. Welcome, Ruichun Dong

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
Fundersnot available
KeywordsVibrationTuning forkThrottleAccelerationFork (system call)Structural engineeringEnvironmental scienceAcousticsMortarEngineeringGeotechnical engineeringMarine engineeringMaterials scienceAutomotive engineeringPhysicsComposite material
DOInot available

Abstract

fetched live from OpenAlex

The vibrations associated with the use of vibrating manure forks are characterized and the vibration exposure time limits based on the recommendations of ANSI S2.70-2006 are estimated. To investigate the vibration exposures associated with these operations, a laboratory study was performed on the vibrations produced by the forks operated during simulated beach cleaning. The test apparatus for the laboratory study consisted of a mortar-mixing tub filled with a homogenous mixture of moist sand and debris. Vibration data were collected for eight seconds per trial. ANOVA results indicate that the mean acceleration for the fast fork was significantly higher than that for the slow fork. The slow fork with the mesh basket could be operated at full throttle for almost three hours before reaching the action value.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.014
GPT teacher head0.216
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

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 designBench or experimental
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
Published2011
Admission routes1
Has abstractyes

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