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Record W4410054345 · doi:10.1139/tcsme-2024-0244

Global curvature characteristics analysis of offset ZI worm drive

2025· article· en· W4410054345 on OpenAlexvenueno aff
Yaoting Yu, Yaping Zhao, Jiayue Ma, Zhiqiang Hao

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCurvatureOffset (computer science)Worm driveComputer sciencePhysicsEngineeringControl theory (sociology)Structural engineeringGeometryMathematicsControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

A new contacting performance index, the global induced principal curvature (GIPC), is put forward in this paper, along with its calculation method. This new index can be used to analyze the global curvature characteristics within the conjugating region of the gearing, so that the contacting performance of the gearing can be understood. A novel type of gearing named offset ZI worm drive is laid out. The calculation method of this new index is applied to this novel type of gearing. The GIPC of this new gearing is calculated by the numerical method and verified by the analytical method; the global curvature characteristics are analyzed. The numerical results show that the absolute value of the GIPC of the e-flank is 52.2384% smaller than the i-flank, which indicates the contact stress level of the e-flank is lower than the i-flank. The maximum of the relative errors for the GIPC between the numerical method and the analytical method is −3.0380e-11%. The accuracy of the numerical method is high.

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 score0.985
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicModular Robots and Swarm IntelligenceFrench-language works237,207