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High Resolution Localization Using Lock-in Based Electron Beam Methods

2017· article· en· W2751758248 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 · 2017
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsCathode rayMaterials scienceBeam (structure)Lock (firearm)Resolution (logic)ElectronElectron beam-induced currentTransistorRoot causeOpticsOptoelectronicsImage resolutionComputer sciencePhysicsElectrical engineeringEngineeringSiliconVoltage

Abstract

fetched live from OpenAlex

Abstract With decreasing transistor sizes accurate failure localization becomes more and more important in order to find the root cause of failures with high efficiency. Field returns are a special challenge, since there is usually only one sample for preparation. Hence, reliable high resolution localization is mandatory for a successful preparation. Optical beam induced resistance change (OBIRCH) is a powerful tool for localization but has resolution limitations due to the diameter of the optical beam. The tool can be further improved by the lock-in technique. In this paper we demonstrate that the lock-in technique can also be applied for electron beam localization methods like electron beam induced current (EBIC) / electron beam absorbed current (EBAC) and resistance change imaging (RCI) / electron beam induced resistance change (EBIRCH).

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.021
GPT teacher head0.287
Teacher spread0.266 · 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