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Record W4237350398 · doi:10.1063/1.4904449.7

10.1063/1.4904449.7

2014· dataset· en· W4237350398 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.

Bibliographic record

VenueDefault Digital Object Group · 2014
Typedataset
Languageen
FieldPhysics and Astronomy
TopicDigital Holography and Microscopy
Canadian institutionsMcGill University
Fundersnot available
KeywordsDigital holographic microscopyHolographyResolution (logic)MicroscopeFlagellumMicroscopyOpticsParameciumBiologyBacteriaMaterials scienceBiological systemPhysicsComputer scienceCell biologyArtificial intelligence

Abstract

fetched live from OpenAlex

Digital holographic microscopy is an ideal tool for investigation of microbial motility. However, most designs do not exhibit sufficient spatial resolution for imaging bacteria. In this study we present an off-axis Mach-Zehnder design of a holographic microscope with spatial resolution of better than 800 nm and the ability to resolve bacterial samples at varying densities over a 380 μm × 380 μm × 600 μm three-dimensional field of view. Larger organisms, such as protozoa, can be resolved in detail, including cilia and flagella. The instrument design and performance are presented, including images and tracks of bacterial and protozoal mixed samples and pure cultures of six selected species. Organisms as small as 1 μm (bacterial spores) and as large as 60 μm (Paramecium bursaria) may be resolved and tracked without changes in the instrument configuration. Finally, we present a dilution series investigating the maximum cell density that can be imaged, a type of analysis that has not been presented in previous holographic microscopy studies.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.018

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 head0.005
GPT teacher head0.229
Teacher spread0.224 · 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