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Record W4246683950 · doi:10.1109/ssp49050.2021.9513842

Table of Contents

2021· article· en· W4246683950 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
FundersAir Force Research LaboratoryOffice of Naval ResearchOffice National d'études et de Recherches AérospatialesShenzhen Research Institute, City University of Hong KongUniversity of California, San DiegoCollege of Engineering, Michigan State UniversityUniversity of Illinois at Urbana-ChampaignUniversitas TelkomUniversität RostockUniversidade Federal do ParanáShenzhen Research Institute of Big DataTechnische Universität IlmenauUniversidad Rey Juan CarlosRWTH Aachen UniversityKorea Advanced Institute of Science and TechnologyUniversité Paris-SaclayTechnische Universität BerlinFreie Universität BerlinUniversidade Estadual de CampinasUniversidad Carlos III de MadridUniversité de BordeauxUniversidad de CantabriaIndian Institute of Technology BombayUniversidade Federal do ParáTechnische Universität MünchenUniversité d'OrléansTélécom ParisUniversidade de São PauloUniversité de MontréalChinese University of Hong KongGoddard Space Flight CenterZhejiang UniversityCentre National de la Recherche ScientifiqueUniversity of RochesterChongqing University of Posts and TelecommunicationsUniversity of Hong KongArizona State UniversityHangzhou Dianzi UniversityInstitut National de la Santé et de la Recherche MédicaleTechnische Universiteit EindhovenInstitut National de Recherche en Sciences et Technologies pour l'Environnement et l'AgricultureLinköpings UniversitetInstitut national de recherche en informatique et en automatique (INRIA)Eidgenössische Technische Hochschule ZürichGeorge Washington UniversityGeorgia Institute of TechnologyRice UniversityTechnische Universität DresdenInstitut Polytechnique de ParisUniversity of Texas at AustinInner Mongolia UniversityChalmers Tekniska HögskolaChongqing UniversityDeakin UniversityTechnische Universiteit DelftNanyang Technological UniversityUniversidade Federal de Santa CatarinaUniversitetet i TromsøImperial College LondonBen-Gurion University of the NegevUniversity of LeicesterPontifícia Universidade Católica do Rio de JaneiroAarhus UniversitetUniversidade Federal do ABCUniversity of LeedsShanghaiTech UniversityGeorgia State UniversityNorth Carolina State UniversityUniversity of WashingtonUniversité du LuxembourgKungliga Tekniska HögskolanErasmus Medisch CentrumWeizmann Institute of SciencePennsylvania State UniversityUniversity of Wisconsin-MadisonHarvard UniversityMassachusetts Institute of Technologyİslam Tarih, Sanat ve Kültür Araştırma MerkeziMichigan State UniversityEmory UniversityHeriot-Watt UniversityUtah State UniversityNorges Teknisk-Naturvitenskapelige UniversitetDalian University of TechnologyPurdue University
KeywordsComputer scienceTable (database)Information retrievalDatabase

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.099
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0020.000
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.9010.865

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 head0.070
GPT teacher head0.200
Teacher spread0.130 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2021
Admission routes1
Has abstractno

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