Record W4313563289 · doi:10.1109/vppc55846.2022.10003414

Reviewers

2022· article· en· W4313563289 on OpenAlexfundno aff

Bibliographic record

Venue2022 IEEE Vehicle Power and Propulsion Conference (VPPC) · 2022

Typearticle

Languageen

Field

Topic

Canadian institutionsnot available

FundersFundação para a Ciência e a TecnologiaCalifornia State University, SacramentoCity, University of LondonRégion NormandieTechnische Universität DortmundThai Nguyen University of TechnologyIndian Institute of Technology MandiShahid Rajaee Teacher Training UniversityUniversidade do MinhoIndian Institute Of Petroleum, Council of Scientific and Industrial Research, IndiaShanghai Ocean UniversitySoutheast UniversityInstituto de TelecomunicaçõesUniversità degli Studi di ParmaNanjing UniversityUniversidade Nova de LisboaTechnische Universität IlmenauNanjing University of Posts and TelecommunicationsIndian Institute of Technology DelhiPolitecnico di TorinoUniversidade do PortoUniversidad Industrial de SantanderKharazmi UniversityUniversidad de OviedoInstituto Superior TécnicoTechnische Universität MünchenArgonne National LaboratoryCalifornia State University, FresnoZhejiang UniversityVrije Universiteit BrusselShanghai Jiao Tong UniversityUniversità degli Studi di PadovaClemson UniversityTechnische Universiteit EindhovenTongji UniversityChina Three Gorges UniversityPennsylvania State UniversitySheffield Hallam UniversityUniversität SiegenSouthwest Jiaotong UniversityUniversité Gustave EiffelSan José State UniversityUniversité de LilleKorea UniversityUniversity of TokyoUniversity of California, DavisUniversidade da Beira InteriorUniversity of SurreyNational University of SingaporeUniversité de SherbrookeUniversità di PisaUniversité du Québec à Trois-RivièresAmrita Vishwa Vidyapeetham UniversityWest Virginia UniversityUniversity of California MercedUniversité de Caen NormandieTrường Đại học Bách Khoa Hà NộiUniversity of OklahomaImperial College LondonUniversità degli Studi di Napoli Federico IITallinna TehnikaülikoolTel Aviv UniversityUniversidade Estadual PaulistaTechnische Universität BerlinNanyang Technological UniversityUniversidade de CoimbraLinyi UniversityDeutsches Zentrum für Luft- und Raumfahrt

KeywordsComputer science

DOI10.1109/vppc55846.2022.10003414

Abstract

fetched live from OpenAlex

No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.006

metaresearch head score (Gemma)0.061

Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated

Candidate categoriesInsufficient payload (model declined to judge)

Consensus categoriesnone

DomainCandidate signal: none · Consensus signal: none

Study designCandidate signal: Not applicable · Consensus signal: Not applicable

GenreCandidate signal: Other · Consensus signal: Other

Teacher disagreement score0.458

Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

Category	Codex	Gemma
Metaresearch	0.006	0.061
Meta-epidemiology (narrow)	0.001	0.001
Meta-epidemiology (broad)	0.001	0.001
Bibliometrics	0.006	0.003
Science and technology studies	0.003	0.001
Scholarly communication	0.009	0.003
Open science	0.002	0.003
Research integrity	0.003	0.003
Insufficient payload (model declined to judge)	0.542	0.329

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 head0.027

GPT teacher head0.267

Teacher spread0.240 · 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