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Record W2186016461 · doi:10.33549/physiolres.931937

In Situ Assessment of the Brain Microcirculation in Mechanically-Ventilated Rabbits Using Sidestream Dark-Field (SDF) Imaging

2011· article· en· W2186016461 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

VenuePhysiological Research · 2011
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMicrocirculationBiomedical engineeringMedicineCerebral blood flowRadiologyAnesthesia

Abstract

fetched live from OpenAlex

Assessment of the cerebral microcirculation by on-line visualization has been impossible for a long time. Sidestream dark-field (SDF) imaging is a relatively new method allowing direct visualization of cerebral surface layer microcirculation using hand-held probe for direct contact with target tissue. The aim of this study was to elucidate the feasibility of studying the cerebral microcirculation in situ by SDF imaging and to assess the basic cerebral microcirculatory parameters in mechanically ventilated rabbits. Images were obtained using SDF imaging from the surface of the brain via craniotomy. Clear high contrast SDF images were successfully obtained. Total small-vessel density was 14.6+/-1.8 mm/mm(2), total all-vessel density was 17.9+/-1.7 mm/mm(2), DeBacker score was 12.0+/-1.6 mm(-1) and microvascular flow index was 3.0+/-0.0. This method seems to be applicable in animal studies with possibility to use SDF imaging also intraoperatively, providing unique opportunity to study cerebral microcirculation during various experimental and clinical settings.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.193
GPT teacher head0.429
Teacher spread0.236 · 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