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Record W4386542750 · doi:10.1002/anbr.202300018

Development of 3D‐Printed Magnetic Micro‐Nanorobots for Targeted Therapeutics: the State of Art

2023· article· en· W4386542750 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 NanoBiomed Research · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of Saskatchewan
FundersChina Scholarship Council
KeywordsNanoroboticsRobotComputer scienceNanotechnologyState of artSystems engineeringEngineeringMaterials scienceArtificial intelligenceData science

Abstract

fetched live from OpenAlex

Micro‐/nanorobots (mn‐robots), inspired by the versatile mechanisms found in natural microorganisms, show great potential in enabling innovative bio‐applications. The 3D‐printed magnetic mn‐robots are substantially advanced to swim in vivo and to carry and release therapeutic agents in a controlled manner. To understand the state of the art of such robots and identify their development trend, this article presents a comprehensive and systematic review of the recent works on development of magnetic robots and their applications in biomedical engineering, with a particular focus on targeted therapeutic delivery. The developments in materials, fabrications, actuations, and applications with design for magnetic mn‐robots are reviewed, and it is aimed to discover the limitations of the existing works and to identify the knowledge gap, thereby deriving future research directions on developing magnetic mn‐robots, especially for their applications in targeted therapeutic delivery.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.050
GPT teacher head0.357
Teacher spread0.306 · 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