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Record W4247615369 · doi:10.1109/mmm.2014.2309399

2013 MTT-S Graduate Student Fellowship Awards [Education News]

2014· article· en· W4247615369 on OpenAlexaff
Giovanni Crupi, Roger Kaul, Changzhi Li, Dominique Schreurs

Bibliographic record

VenueIEEE Microwave Magazine · 2014
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsGraduate studentsLibrary scienceMedical educationEngineeringGraduate researchEngineering managementPolitical scienceComputer scienceMedicine

Abstract

fetched live from OpenAlex

The IEEE Microwave Theory and Techniques Society (MTT-S) Graduate Student Fellowship Awards are sponsored by the MTT-S for the purpose of encouraging and supporting graduate students from around the world interested in pursuing the field of microwave engineering. The graduate fellowship recipients receive an award of US$6,000 to support their research activities, which is presented at the annual IEEE MTT-S International Microwave Symposium (IMS). Supplemental travel funding is offered to the recipients to support their travel to the IMS. Ten graduate fellowships were awarded in 2013 in the general category and three in the medical applications category. In 2013, 25 applications from 12 countries were received in the general category, and eight applications from four countries were received in the medical applications category. The applications were excellent and represented some of the best research being conducted around the world. Even with the additional medical applications award, the success rate was only about 40% due to the large number of submissions. The 13 awardees and their projects are described.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.243
Teacher spread0.226 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2014
Admission routes1
Has abstractyes

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