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Record W2597556205

D6.3 Intermediate system evaluation results

2014· article· en· W2597556205 on OpenAlexaboutno aff
Petar Popovski, G. Mange, P. Fertl, Damián Serrano, H. Droste, N. Bayer, Adrian Roos, T. Rosowski, G. Zimmermann, P. Agyapong, Mikael Fallgren, Ning He, Anders Höglund, J. Söder, H. Tullberg, S. Jeux, O. Bulakci, Joseph K. Eichinger, M. Schellmann, J. Lianghai, Andri Rauch, Alexander Klein, M.G. Stamatelatos, Z. Li, M. Moisio, M. Maternia, E. Lähetkangas, K. Pawlak, José Francisco Monserrat del Río, David Martín-Sacristán Gandía

Bibliographic record

VenueRiuNet (Politechnical University of Valencia) · 2014
Typearticle
Languageen
FieldEngineering
TopicEngineering Applied Research
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

The overall purpose of METIS is to develop a 5G system concept that fulfil s the requirements of the beyond-2020 connected information society and to extend today’s wireless communication systems for new usage cases. First, in this deliverable an updated view on the \noverall METIS 5G system concept is presented. \nThereafter, simulation results for the most promising technology components supporting the METIS 5G system concept are reported. \nFinally, s \nimulation results are presented for \none \nrelevant \naspect of each Horizontal Topic: \nDirect Device \n- \nto \n- \nDevice Communication, Massive Machine Communication, Moving Networks, \nUltra \n- \nDense Networks, and Ultra \n- \nReliable Communication.

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)0.011
metaresearch head score (Gemma)0.021
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.006

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 head0.011
GPT teacher head0.204
Teacher spread0.192 · 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
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

Citations1
Published2014
Admission routes1
Has abstractyes

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