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Record W2807288411 · doi:10.11159/cdsr18.124

A Do-and-See Approach for Learning Mechatronics Concepts

2018· article· en· W2807288411 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 of the International Conference of Control, Dynamic systems, and Robotics · 2018
Typearticle
Languageen
FieldEngineering
TopicMechatronics Education and Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMechatronicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This paper describes a low-cost approach for teaching mechatronic concepts to undergraduate engineering students. The laboratory unit includes a wide range of mechatronics related subjects, including computer interfacing, design, prototyping, controller implementation, mechanism synthesis and analysis and, hardware-in-the-loop simulations. The students are given a shoebox filled with all needed materials with the goal of completing several projects with clear objectives. The students can plan and accomplish the goals in many ways, and will gain greater technical skills sooner and become technically more mature. For the experiments described in this paper, prototyping and control of a 5-link parallel robot to follows a planar trajectory is described as a project.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.361

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)0.0000.000

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 head0.020
GPT teacher head0.268
Teacher spread0.248 · 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