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Record W1966364439 · doi:10.1117/12.2079625

Adaptation of commercial microscopes for advanced imaging applications

2015· article· en· W1966364439 on OpenAlexaff
Craig Brideau, Kelvin W. C. Poon, Peter K. Stys

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAdaptation (eye)MicroscopeComputer scienceMicroscopyOpticsPhysics

Abstract

fetched live from OpenAlex

Today’s commercially available microscopes offer a wide array of options to accommodate common imaging experiments. Occasionally, an experimental goal will require an unusual light source, filter, or even irregular sample that is not compatible with existing equipment. In these situations the ability to modify an existing microscopy platform with custom accessories can greatly extend its utility and allow for experiments not possible with stock equipment. Light source conditioning/manipulation such as polarization, beam diameter or even custom source filtering can easily be added with bulk components. Custom and after-market detectors can be added to external ports using optical construction hardware and adapters. This paper will present various examples of modifications carried out on commercial microscopes to address both atypical imaging modalities and research needs. Violet and near-ultraviolet source adaptation, custom detection filtering, and laser beam conditioning and control modifications will be demonstrated. The availability of basic ‘building block’ parts will be discussed with respect to user safety, construction strategies, and ease of use.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.748

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 science0.0010.000
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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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 teacher head, 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
Published2015
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Fluorescence Microscopy TechniquesFrench-language works237,207