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Record W4324319564 · doi:10.1117/12.2648999

Design and fabrication of a GRIN-axicon for Bessel-Gauss beam generation and applications to fast volumetric imaging (Conference Presentation)

2023· article· en· W4324319564 on OpenAlexaff
Mireille Quémener, Pierre Girard-Collins, Alexandra Alain-Beaudoin, Nicolas Grégoire, Steeve Morency, Michèle Desjardins, Daniel Côté, Simon Thibault

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversité LavalInstitut National d'Optique
Fundersnot available
KeywordsAxiconBessel beamOpticsDepth of fieldLens (geology)Bessel functionMicroscopeField of viewMaterials sciencePhysicsComputer scienceLaserLaser beams

Abstract

fetched live from OpenAlex

We introduce the GRIN-axicon, a new low-cost optical component that is easy to manufacture and could replace the axicon in various setups such as a two-photon microscope. In neuroscience, the imaging of in vivo samples requires high temporal resolution in order to capture the interactions between neurons located at different depths in the tissue. To achieve this, the use of an axicon lens increases the depth of field of the microscope and reduces the number of scans to be performed. However, the axicon is difficult to manufacture and generally has defects on the tip of the cone, thus degrading the quality of the resultant Bessel-Gauss beam.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.006

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 head0.028
GPT teacher head0.323
Teacher spread0.295 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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