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Record W2084928524 · doi:10.1088/0960-1317/17/9/e01

The 6th International Workshop on Micro and Nanotechnologies for Power Generation and Energy Conversion Applications (PowerMEMS 2006)

2007· article· en· W2084928524 on OpenAlexaff
Luc G. Fréchette

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2007
Typearticle
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsUSableElectronicsEngineeringSystems engineeringWork (physics)NanotechnologyComputer scienceElectrical engineeringMechanical engineeringMaterials science

Abstract

fetched live from OpenAlex

Energy is a sector of paramount importance over the coming decades if we are to ensure sustainable development that respects our environment. The research and development of novel approaches to convert available energy into usable forms using micro and nanotechnologies can contribute towards this goal and meet the growing need for power in small scale portable applications. The dominant power sources for handheld and other portable electronics are currently primary and rechargeable batteries. Their limited energy density and adverse effects on the environment upon disposal suggest that alternative approaches need to be explored. This special issue will showcase some of the leading work in this area, initially presented at PowerMEMS 2006, the 6th International Workshop on Micro and Nanotechnologies for Power Generation and Energy Conversion Applications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.380

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2007
Admission routes1
Has abstractyes

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