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Record W4383621304 · doi:10.1002/aisy.202300168

Actuation of Mobile Microbots: A Review

2023· review· en· W4383621304 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

VenueAdvanced Intelligent Systems · 2023
Typereview
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsHyperion Technologies (Canada)
Fundersnot available
KeywordsMiniaturizationComputer scienceRoboticsActuatorFocus (optics)Human–computer interactionRobotSystems engineeringNanotechnologyArtificial intelligenceEngineeringMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Maturation of robotics research and advances in the miniaturization of machines have contributed to the development of microbots and enabled new technological possibilities and applications. Microbots have a wide range of applications, including the navigation of confined spaces, environmental monitoring, micro‐assembly and manipulation of small objects, and in vivo micro‐surgeries and drug delivery. Actuators are among the most critical components that define the performance of robots. A comprehensive review of the actuation mechanisms that have been employed in mobile microbots is provided, including piezoelectric, magnetic, electrostatic, thermal, acoustic, biological, chemical, and optical actuation, with a focus on the most recent development and methodologies.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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)0.0000.001

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 head0.064
GPT teacher head0.380
Teacher spread0.316 · 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