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Record W2149393966 · doi:10.1117/1.jbo.20.5.056001

Image distortion and its correction in linear galvanometric mirrors–based laser-scanning microscopy

2015· article· en· W2149393966 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Biomedical Optics · 2015
Typearticle
Languageen
FieldEngineering
TopicImage Processing Techniques and Applications
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersCIHR Skin Research Training CentreCanadian Institutes of Health ResearchUniversity of British ColumbiaCanadian Dermatology Foundation
KeywordsOpticsMicroscopyDistortion (music)LaserMaterials scienceOptical microscopeLaser scanningScanning electron microscopePhysicsOptoelectronics

Abstract

fetched live from OpenAlex

To simplify imaging focusing and calibration tasks, a laser-scanning microscope needs to scan ata moderate frame rate. The inertia of a galvanometric scanner leads to time delays when following external commands, which subsequently introduces image distortions that deteriorate as scan frequency increases. Sinusoidal and triangular waveforms were examined as fast axis driving patterns. The interplay among driving pattern, frequency, sampling rate, phase shift, linear scanning range, and their effect on reconstructed images was discussed. Utilizing position feedback from the linear galvo scanners, the effect of response time could be automatically compensated in real time. Precompensated triangular driving waveform offered the least amount of image distortion.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.300
Teacher spread0.279 · 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