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Record W7155074984 · doi:10.5281/zenodo.19672969

Dataset for "Experimental investigation of twin pulsed jets in a hemispheric elastic cavity"

2023· dataset· en· W7155074984 on OpenAlexaff
Lara-Sofia Merlo, Lyes Kadem, Wael Saleh, Hoi Dick Ng, Giuseppe Di Labbio

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsÉcole de Technologie SupérieureConcordia University
Fundersnot available
KeywordsMATLABRaw dataField (mathematics)Experimental dataData processing

Abstract

fetched live from OpenAlex

This dataset contains the raw velocity field data supporting the results presented in the article “Experimental investigation of twin pulsed jets in a hemispheric elastic cavity.” The dataset consists of time-resolved velocity fields obtained from experimental measurements of twin pulsed jets interacting within a hemispheric elastic cavity. The velocity fields are provided as MATLAB (.mat) files. The dataset is organized into five ZIP folders, each corresponding to a specific formation time. Within each folder, there are four MATLAB (.mat) files representing different spacing ratios between the twin pulsed jets. Each .mat file contains a structure named “vel” that stores the velocity field data. The structure includes velocity components vel.u and vel.v, corresponding to the x- and y-direction velocity components, respectively, defined over space and time. These raw data were used to generate the figures and results presented in the manuscript. For details on the experimental setup, measurement techniques, and data processing methods, refer to the associated publication.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0330.053

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 head0.057
GPT teacher head0.293
Teacher spread0.236 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)→French-language works237,207→