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Record W2952739892 · doi:10.1038/s41598-018-21543-2

A dual-mode mobile phone microscope using the onboard camera flash and ambient light

2018· article· en· W2952739892 on OpenAlexfundno aff
Antony Orth, Emma R. Wilson, Jeremy G. Thompson, Brant C. Gibson

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldEngineering
TopicImage Processing Techniques and Applications
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilRMIT UniversityARC Centre for Nanoscale BioPhotonicsOntario Ministry of Natural Resources and Forestry
KeywordsFlash (photography)MicroscopeDual modeComputer scienceMobile phoneDual (grammatical number)PhoneCamera phoneMode (computer interface)Computer graphics (images)MicroscopyComputer visionOpticsArtificial intelligenceTelecommunicationsPhysicsHuman–computer interactionArtEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

Mobile phone microscopes are a natural platform for point-of-care imaging, but current solutions require an externally powered illumination source, thereby adding bulk and cost. We present a mobile phone microscope that uses the internal flash or sunlight as the illumination source, thereby reducing complexity whilst maintaining functionality and performance. The microscope is capable of both brightfield and darkfield imaging modes, enabling microscopic visualisation of samples ranging from plant to mammalian cells. We describe the microscope design principles, assembly process, and demonstrate its imaging capabilities through the visualisation of unlabelled cell nuclei to observing the motility of cattle sperm and zooplankton.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

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 science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.010
GPT teacher head0.268
Teacher spread0.258 · 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

Citations74
Published2018
Admission routes1
Has abstractyes

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