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Record W2296190451 · doi:10.1002/jbio.201500261

Motion‐free endoscopic system for brain imaging at variable focal depth using liquid crystal lenses

2016· article· en· W2296190451 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 Biophotonics · 2016
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsFocal lengthOpticsLiquid crystalPolarization (electrochemistry)Materials scienceVoltageFocal adhesionOptical imagingBiomedical engineeringOptoelectronicsPhysicsChemistryMedicine

Abstract

fetched live from OpenAlex

We present a motion-free system for microendoscopic imaging of biological tissues at variable focal depths. Fixed gradient index and electrically tunable liquid crystal lenses (TLCL) were used to build the imaging optical probe. The design of the TLCL enables polarization-independent and relatively low-voltage operation, significantly improving the energy efficiency of the system. A focal shift of approximately 74 ± 3 µm could be achieved by electrically controlling the TLCL using the driving frequency at a constant voltage. The potential of the system was tested by imaging neurons and spines in thick adult mouse brain sections and in vivo, in the adult mouse brain at different focal planes. Our results indicate that the developed system may enable depth-variable imaging of morpho-functional properties of neural circuitries in freely moving animals and can be used to investigate the functioning of these circuitries under normal and pathological conditions.

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 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 score0.027
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.048
GPT teacher head0.309
Teacher spread0.261 · 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