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Record W1607636450 · doi:10.4271/2000-01-2677

WIzARD: Weld Inspection And Reporting Database Software development, implementation, and application

2000· article· en· W1607636450 on OpenAlexaff
Campbell Steven Piper

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2000
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsChrysler (Canada)
Fundersnot available
KeywordsWizardComputer scienceDatabaseSoftware engineeringSoftwareSoftware developmentEngineering drawingEngineeringProgramming languageWorld Wide Web

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph"><b>A relational database created for biw resistance spotweld program. Graphics and data are combined to provide clear and accurate information to cross functional welding teams (inspection, production, maintenance, engineering). System is networked across the biw to enable timely communication of issues. Online input and updating allows tracking of process parameters and assists in continuous improvement. “from-the-floor” documentation creates useful short/long term statistical process control and “hot-spot” identification. Dramatic improvments in team response time, coordination, and lower operating costs through continuous improvement and reduced reprocessing.</b></div>

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
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
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.256
Teacher spread0.244 · 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.

Study designObservational
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

Citations0
Published2000
Admission routes1
Has abstractyes

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