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Record W2994742208 · doi:10.1109/omn.2019.8925013

1D LiDAR Based on Large Aperture FPCB Mirror

2019· article· en· W2994742208 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

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsLidarOpticsElectromagnetic coilFabricationLaserMaterials scienceFlexible electronicsFocal pointOptoelectronicsElectrical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

This paper presents a Lorentz force FPCB (flexible printed circuit board) mirror based LiDAR. The driving coil and torsion beam are fabricated using low cost commercial FPCB fabrication process. A thin silicon mirror plate coated with aluminum is attached on top of the middle of the FPCB structure. External magnets on both sides and the current through the coil generate Lorentz fore to rotate the FPCB mirror. The oscillating FPCB mirror is combined with a single point LiDAR to achieve a scanning 1D LiDAR. The mirror plate steers the emitted laser beam, collects the diffuse reflected light and reflects to the receiver of the single point LiDAR. The achieved performance of the scanning LiDAR is: field of view-60°, 500 points, refreshing 10 kHz, distance 40 meters with an error of 10 cm.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.005
GPT teacher head0.234
Teacher spread0.229 · 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

Quick stats

Citations11
Published2019
Admission routes1
Has abstractyes

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