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Record W3033184624 · doi:10.1002/jbio.202070017

Inside Cover: Efficient and cost‐effective 3D cellular imaging by sub‐voxel‐resolving light‐sheet add‐on microscopy

2020· paratext· en· W3033184624 on OpenAlexaff
Fang Zhao, Yicong Yang, Yi Li, Hao Jiang, Xinlin Xie, Tingting Yu, Xuechun Wang, Qing Liu, Hao Zhang, Haibo Jia, Sheng Liu, Mei Zhen, Dan Zhu, Shangbang Gao, Peng Fei

Bibliographic record

VenueJournal of Biophotonics · 2020
Typeparatext
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsVoxelLight sheet fluorescence microscopyMicroscopyFluorescence microscopeCover (algebra)ThroughputBiological specimenMicroscopeOpticsMaterials scienceNanotechnologyComputer visionComputer scienceFluorescencePhysicsEngineering

Abstract

fetched live from OpenAlex

Abstract A type of compact and cost‐effective light‐sheet imaging device, termed sub‐voxel‐resolving light‐sheet add‐on module (SLAM), is developed to cooperate with conventional 2D epifluorescence microscope, allowing high‐contrast, resolution‐improved 3D imaging of various biological samples at high throughput. Further details can be found in the article by Fang Zhao, Yicong Yang, Yi Li, et al. ( e201960243 ). image

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 categoriesMeta-epidemiology (narrow)
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 score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.004
GPT teacher head0.253
Teacher spread0.250 · 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.

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
Published2020
Admission routes1
Has abstractyes

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