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Record W4416884873 · doi:10.37665/srjyovr63054

Improving Product Reliability Using Accelerated Stress Testing

2012· article· W4416884873 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

VenueSoldering and Reliability Conferences · 2012
Typearticle
Language
FieldEngineering
TopicReliability and Maintenance Optimization
Canadian institutionsSciex (Canada)Spinal Cord Injury BCNorth Toronto Eye Care
Fundersnot available
KeywordsReliability (semiconductor)Accelerated life testingFailure rateField (mathematics)Component (thermodynamics)Stress (linguistics)Stress testing (software)Failure mode and effects analysis

Abstract

fetched live from OpenAlex

ABSTRACT Two electronics subsystems were subjected to highly accelerated life testing (HALT) involving thermal and vibration stresses to determine the operating and destruct limits, and to discover potential design, component and manufacturing related weaknesses. Several failure modes were discovered and some of the failing components were by-passed to enable testing at higher stress levels. The HALT operating limits were used to estimate the failure rate of each subsystem under normal operating conditions using a model based on a correlation of field data and HALT results for similar electronic products.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.487
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0010.001
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 head0.047
GPT teacher head0.256
Teacher spread0.208 · 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