MétaCan
Menu
Back to cohort

Dynamic Electroluminescence Imaging (DEI) as an “Optical Oscilloscope” Probe

2005· article· en· W3114744922 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

VenueProceedings - International Symposium for Testing and Failure Analysis · 2005
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsOscilloscopeWaveformBandwidth (computing)Computer scienceElectroluminescenceElectronic engineeringTransmission (telecommunications)SIGNAL (programming language)Radio frequencyElectronic circuitElectrical engineeringOptoelectronicsMaterials scienceVoltageEngineeringTelecommunicationsDetector

Abstract

fetched live from OpenAlex

Abstract Dynamic Electroluminescence Imaging (DEI) is a technique used to observe semiconductor devices as they operate. Much like a traditional oscilloscope, the technique delivers waveform information that is useful for assessing the operation of the circuits that comprise a device. It can be thought of as a non-contact “optical oscilloscope probe”. The technique has two major advantages over traditional electrical oscilloscope probing. The technique is noninvasive and has a theoretical bandwidth approaching 100 GHz. This means that very fast signals can be observed without unduly loading or otherwise interfering with the circuitry under test. Moreover, the characterization of signals at individual nodes along a signal path allows problems that arise from intervening interconnects and transmission lines to be identified. This paper will show several examples of the radio frequency (RF) measurement capabilities of this technique that have been demonstrated in our laboratory.

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 score0.975
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.228
Teacher spread0.222 · 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