MétaCan
Menu
Back to cohort
Record W2108556597 · doi:10.1109/tmech.2006.878543

Design and evaluation of a micro-fuel-cell-based power system for a mobile robot

2006· article· en· W2108556597 on OpenAlexaff
Alexander Wilhelm, Brian Surgenor, Jon G. Pharoah

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsBattery (electricity)Proton exchange membrane fuel cellFuel cellsMechatronicsAutomotive engineeringRobotLead–acid batteryMobile robotPower (physics)Hydrogen fuelElectrolyteEngineeringComputer scienceElectrical engineeringProcess engineeringSimulationChemical engineeringChemistryArtificial intelligenceElectrode

Abstract

fetched live from OpenAlex

A mobile robot being used for an undergraduate course in mechatronics engineering was converted from a conventional lead acid battery to a hydrogen fuelled polymer electrolyte membrane (PEM) micro fuel cell as the power source. The application of the robot is first outlined. Next, the design of the fuel-cell-based power supply system as assembled from the commercial components is described. Finally, the performance of the fuel cell is documented. The performance was found to match that of the conventional battery. An operational problem associated with the purging of water had to be solved. Although the cost of the fuel cell was 50 times that of the battery, the exercise did serve to demonstrate the potential of the technology

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.267
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations27
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueIEEE/ASME Transactions on MechatronicsSame topicAdvanced Battery Technologies ResearchFrench-language works237,207