MétaCan
Menu
Back to cohort
Record W4320030810 · doi:10.1109/mpel.2022.3222599

Brainstorming for Game-Changing Ideas

2022· article· en· W4320030810 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Power Electronics Magazine · 2022
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsBrainstormingSession (web analytics)Power (physics)Computer scienceWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

This year, the IEEE Future of Electronic Power Processing and Conversion (FEPPCON) XI held in Reykjavik, Iceland, 3–7 June 2022, added a new form of technical session called “Brainstorming for Game-Changing Ideas” through poster presentations and discussions, initiated by the late past president of IEEE Power Electronics Society (PELS) Braham Ferreira. The workshop participants were encouraged to think out-of-the box, identifying game-changing ideas or technology gaps to achieve lofty goals relevant to power electronics. A call for posters was issued to all workshop participants and 11 posters were received, describing big ideas leading to technological breakthroughs or gaps before achieving these advances. The posters were posted to the workshop participants and judged by a small committee as well as voted by all attendees. Four winning posters were selected and their authors presented their summaries to the participants, followed by discussions. The four winning posters are:

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
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)0.0000.000

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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