MétaCan
Menu
Back to cohort
Record W4376457040 · doi:10.2316/j.2023.206-0874

DESIGN OF REVERSE THRUST ADSORPTION WALL-CLIMBING ROBOT BASED ON TRIZ AND INPD FUSION, 441-449.

2023· article· en· W4376457040 on OpenAlexvenueno aff
Minglu Chi, Shuaibing Chang, Ruihua Ren, Jinyu Wang, Xueyan Sun, Jiawen Jia, Xiaoyan Qian

Bibliographic record

VenueInternational Journal of Robotics and Automation · 2023
Typearticle
Languageen
FieldEngineering
TopicExtenics and Innovation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsTRIZThrustRobotClimbingComputer scienceEngineeringMechanical engineeringArtificial intelligenceStructural engineering

Abstract

fetched live from OpenAlex

To address the problems related to the cleaning of building exteriorwalls, a reverse thrust adsorption wall-climbing robot (RTAWCR)is designed by combining the theory of inventive problem solving(TRIZ) and integrated new product development (INPD) methods.

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)0.001
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 score0.824
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.031
GPT teacher head0.285
Teacher spread0.254 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Robotics and AutomationSame topicExtenics and Innovation MethodsFrench-language works237,207