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Record W7161258004 · doi:10.5281/zenodo.20200673

Wireless EV Charging Session Measurements – Static WPT Testbench Dataset (OPEVA Project)

2025· dataset· W7161258004 on OpenAlexaff
Mehmet Ogün Tanağardı, I. Yasin Simşek, Muhammed Fatih Özkaya, Cengiz Bektaş, Alper Kanak, Salih Ergün

Bibliographic record

VenueOpen MIND · 2025
Typedataset
Language
Field
Topic
Canadian institutionsSemtech (Canada)
FundersEuropean Commission
KeywordsSession (web analytics)RangingWirelessElectromagnetic coilCurrent (fluid)Baseline (sea)

Abstract

fetched live from OpenAlex

This release includes all wireless EV charging session data collected on the static WPT testbench at Ümraniye, covering coil gap distances of 20, 40, 60, and 80 mm at SoC levels of 20% and 80%. Measurements are logged at 5-second intervals across sessions ranging from 30 to 480 minutes. Primary-side and secondary-side electrical measurements are real for all configurations. Charger output current at 60 mm and 80 mm gaps is synthetically estimated using an efficiency model derived from 20 mm baseline sessions — methodology documented in the README. Includes session_parameters.csv for session metadata and data/columns.json for machine-readable schema.

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)0.003
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 score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0180.038

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 head0.152
GPT teacher head0.412
Teacher spread0.260 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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