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Record W2921169316 · doi:10.1115/1.4042958

Special Section: Selected Papers From IDETC 2018

2019· article· en· W2921169316 on OpenAlexaff
Clément Gosselin, Pierre Larochelle, Andreas Müller

Bibliographic record

VenueJournal of Mechanisms and Robotics · 2019
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsGratitudeRoboticsPresentation (obstetrics)Computer scienceArtificial intelligenceScheduleModular designRobotSpecial sectionEngineeringMedicinePsychology

Abstract

fetched live from OpenAlex

For 42 years, the Mechanisms and Robotics (M&R) Conference has provided an international venue for presentation and discussion of the latest scientific and technical results in the broad field of mechanical systems and their applications. This includes the design (novel mechanisms and robots, synthesis), analysis (kinematics, dynamics, computational approaches, and software systems), applications (from micro-air vehicles, modular robotics, origami applications, medical robotics, to exoskeleton-assistive systems), and educational practices. This fifth IDETC Special Issue contains selected papers from active researchers that have presented results of archival value. The reader will appreciate the wide span of topics showcasing the diversity and quality of the symposia that were organized within the M&R conference.We would like to express our sincere gratitude to the editor Professor Venkat Krovi for his guidance and support during our editorial work. We are also grateful to the reviewers who have dedicated their time and effort to ensure the quality of the journal within a tight schedule.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.251
Threshold uncertainty score0.349

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 head0.005
GPT teacher head0.181
Teacher spread0.176 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2019
Admission routes1
Has abstractyes

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