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Record W2514928272 · doi:10.1109/iscas.2016.7527379

Low-cost trimmable manufacturing methods for printable electronics

2016· article· en· W2514928272 on OpenAlexaffabout
Adam Gordon, Gordon W. Roberts, Christian Fayomi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsUniversité du Québec à MontréalMcGill University
Fundersnot available
KeywordsElectronicsManufacturing engineeringComponent (thermodynamics)Construct (python library)Work (physics)Manufacturing costElectronic component3D printingComputer scienceInkwellYield (engineering)EngineeringElectrical engineeringMechanical engineeringMaterials science

Abstract

fetched live from OpenAlex

While printable electronics (PE) has the potential to provide a low cost means to manufacture electronic solutions, it suffers serious levels of component variations. While many of the problems facing PE are early technological development yield-related problems, some are more fundamental to its manufacturing nature. In this work, methods to construct PE circuits that compensate for these variations will be described. These methods include a combination of printing, severing, and ink deposition techniques that are performed both during and after manufacturing. Data obtained from working prototypes made using the PE technology at the National Research Council (NRC) of Canada will be 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.484
Threshold uncertainty score0.308

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 head0.015
GPT teacher head0.280
Teacher spread0.265 · 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
GenreMethods

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

Citations4
Published2016
Admission routes2
Has abstractyes

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