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MWP 2020 Technical Program

2020· article· en· W4246352428 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDentistry
TopicScientific and Engineering Research Topics
Canadian institutionsnot available
FundersNational Institute of Information and Communications TechnologyUniversity of Colorado BoulderGoddard Space Flight CenterIran Telecommunication Research CenterNanjing UniversityUniversità di BolognaHokkaido UniversityUniversity of California, Santa BarbaraDalian University of TechnologyAalborg UniversitetUniversitat Politècnica de ValènciaJinan UniversityNational Institute of Standards and TechnologySwinburne University of TechnologyTsinghua UniversityRMIT UniversityMIREA - Russian Technological UniversityStrongUniversidad Carlos III de MadridWaseda UniversityNational Institute of Advanced Industrial Science and TechnologyXi'an Institute of Optics and Precision MechanicsUniversity of HullCentre National de la Recherche ScientifiqueChinese Academy of SciencesNorges Teknisk-Naturvitenskapelige UniversitetJilin UniversityMcGill UniversityUniversity of OttawaNational Aeronautics and Space AdministrationInstitute of Semiconductors, Chinese Academy of SciencesDrexel UniversitySoutheast UniversityMonash UniversityCity University of Hong KongNanjing University of Aeronautics and AstronauticsRensselaer Polytechnic Institute
KeywordsComputer science

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)0.004
metaresearch head score (Gemma)0.004
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 score0.630
Threshold uncertainty score0.899

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3700.334

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 head0.040
GPT teacher head0.331
Teacher spread0.290 · 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
Published2020
Admission routes1
Has abstractno

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