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Record W1974590895 · doi:10.1117/12.686579

Microassembly of 3D micromirrors as building elements for optical MEMS switching

2006· article· en· W1974590895 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

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsUniversity of WaterlooUniversity of Victoria
Fundersnot available
KeywordsMicroelectromechanical systemsProcess (computing)Construct (python library)Computer scienceLock (firearm)Optical switchGrippersKey (lock)RobotMechanical engineeringEngineeringElectronic engineeringMaterials scienceArtificial intelligenceOptoelectronics

Abstract

fetched live from OpenAlex

A robotic-based microassembly process has been successfully applied to the construction of a novel micro-mirror design for use in optical switching. This paper is devoted to the description of the microassembly process used to construct the 3D micro-mirror. The microassembly process is based upon the PMKIL (Passive Microgripper, Key and Inter-Lock) assembly system. Details of the assembly process include, the methodology to construct the micro-mirror, the design of the micro-mirror parts, and the design of the tools (microgrippers) that are mounted to the robot to handle the micro-parts. The results of the assembly process are presented, along with examples of prototype 3D micro-mirrors. The entire 3D micromirror consists of a novel electro-static rotary motor, onto which the 3D mirror structure is assembled. The 3D micro-mirror is used as a building element for 1 N optical switching systems and for N×M optical crossconnects.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.539
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.248
Teacher spread0.238 · 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