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Record W4396634409 · doi:10.1016/j.xpro.2024.103053

Protocol for optical, aqueous-based clearing of murine tissues using EZ Clear

2024· article· en· W4396634409 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSTAR Protocols · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsnot available
FundersNHLBI Division of Intramural ResearchNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Child Health and Human DevelopmentCanadian Institutes of Health ResearchNational Heart, Lung, and Blood InstituteSchool of Medicine, University of VirginiaNational Institutes of Health
KeywordsFluorescenceClearingFixation (population genetics)Protocol (science)Biomedical engineeringEndogenyBiophysicsChemistryComputer scienceCell biologyBiologyPathologyBiochemistryMedicineOptics

Abstract

fetched live from OpenAlex

Tissue clearing is an essential prerequisite for 3D volumetric imaging of larger tissues or organs. Here, we present a detailed protocol for optical, aqueous-based clearing of adult murine tissues using EZ Clear. We describe steps to ensure successful perfusion and fixation of organs from the adult mouse and supply guidelines for optimal lipid removal, refractive index matching, and tissue clearing. Finally, we provide imaging parameters for visualizing both exogenous perfused fluorescent dyes and endogenous fluorescence reporters in the adult mouse. For complete details on the use and execution of this protocol, please refer to Hsu et al.1

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.156
Threshold uncertainty score0.711

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 science0.0000.000
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 head0.051
GPT teacher head0.435
Teacher spread0.384 · 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