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Preface

2019· article· en· W4255896057 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicIndustrial Automation and Control Systems
Canadian institutionsnot available
Fundersnot available
KeywordsChinaLibrary scienceRoboticsControl (management)Political scienceEngineering ethicsArtificial intelligenceEngineering managementManagementEngineeringComputer scienceLawRobot

Abstract

fetched live from OpenAlex

The organizing committee of the 5th International Conference on Electrical Engineering, Control and Robotics (EECR 2019) aimed to facilitate interaction among participants for the latest progress and development in the fields of electrical engineering, control and robotics. Through this conference, the committee intends to enhance the sharing of individual experiences and expertise in electrical engineering, control and robotics with particular emphasis on the technical challenges associated with varied applications in these fields. The conference was held in Xihu Hotel of SCUT, Guangzhou, China, January 12-14, 2019, organized by Sichuan Institute of Electronics with the support of South China University of Technology, University of Electronic Science and Technology of China and Southwest Minzu University. Despite the high quality of most of the submissions, the final proceedings of EECR 2019 includes 62 papers, which were presented at the conference and that were selected after a thorough reviewing process. The authors of these papers come from different countries from Europe, Australia and Asia etc.. The contributions of the technical program committee and the referees are deeply appreciated. Most of all, we would like to express our sincere thanks to the authors for submitting their most recent works and the organizing committee for their enormous efforts to turn this event into a smoothly running meeting. We sincerely hope that this publication will prove to be an important resource for the scientific community. Prof. Chun-Yi Su Concordia University, Canada Jan. 18, 2019

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.514

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 communication0.0000.001
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 head0.010
GPT teacher head0.185
Teacher spread0.174 · 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