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Record W591470574

Implementing an analog speedometer in STISIM Drive using Parallax BSTAMP microcontroller

2008· article· en· W591470574 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

VenueConstellation (Université du Québec à Chicoutimi) · 2008
Typearticle
Languageen
FieldEngineering
TopicEngine and Fuel Emissions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDashboardMicrocontrollerComputer scienceSimple (philosophy)SoftwareParallaxEmbedded systemAutomotive engineeringSimplicitySimulationComputer hardwareEngineeringHuman–computer interactionArtificial intelligenceOperating system
DOInot available

Abstract

fetched live from OpenAlex

In a non-instrumental cab, STISIM Drive software normally projects the speed of the vehicle through a dashboard presented on the simulation screen. The simulated dashboard can be displayed with several graphical options. In all cases, there is a loss of information arising from the road. A solution is to integrate the speedometer into a dashboard and to disable the simulated projection. This solution increases the virtual immersion of the driver and presents speed in a more realistic way. We are proposing a simple solution based on Parallax Inc. Basic Stramp microcontroller. In addition to its low cost and simplicity, this solution allows integration of other technical elements of the driving experience (e.g., activation of turn signals, horn, etc.).

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 categoriesInsufficient payload (model declined to judge)
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 score0.136
Threshold uncertainty score0.996

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)0.0050.000

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 head0.016
GPT teacher head0.201
Teacher spread0.185 · 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