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Record W4235453165 · doi:10.1109/icdcs.2019.00004

Table of contents

2019· article· en· W4235453165 on OpenAlexfundno aff
Parisa Rahimzadeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsnot available
FundersSandia National LaboratoriesOak Ridge National LaboratoryUniversity of Massachusetts AmherstUniversity of California, IrvineDonghua UniversityShanghai Jiao Tong UniversityZhejiang UniversityNorthwest UniversityAmerican University of SharjahAustralian National UniversityUniversity of ConnecticutCity University of Hong KongTowson UniversityPennsylvania State UniversityHuazhong University of Science and TechnologyInstitut national de recherche en informatique et en automatique (INRIA)Case Western Reserve UniversityUniversity of Central FloridaStony Brook UniversityUniversity of WaterlooUniversity of MinnesotaGeorge Mason University
KeywordsTable (database)Computer scienceDatabase

Abstract

fetched live from OpenAlex

The following topics are dealt with: cloud computing; learning (artificial intelligence); resource allocation; Internet of Things; optimisation; mobile computing; distributed processing; Internet; data privacy; computational complexity.

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)0.009
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 score0.227
Threshold uncertainty score0.324

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0020.000
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7730.689

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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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