MétaCan
Menu
Back to cohort
Record W4224229786 · doi:10.1016/j.mex.2022.101694

Craniotomy for acute monitoring of pial vessels in the rodent brain

2022· article· en· W4224229786 on OpenAlexaff
Refat Aboghazleh, Baraah Alkahmous, Evyatar Swissa, Saara Mansoor, Alon Friedman, Ofer Prager

Bibliographic record

VenueMethodsX · 2022
Typearticle
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCraniotomyMedicineParenchymaBlood–brain barrierPathologyIntravital microscopyRadiologyCentral nervous systemMicrocirculationInternal medicine

Abstract

fetched live from OpenAlex

A growing awareness for vascular contribution to pathogenesis of brain diseases increases the need for techniques that allow high-resolution imaging and quantification of changes in function and structure of cerebral microvessels. Cerebral vessels are very sensitive structures, making them vulnerable for injury. In addition, they are uniquely characterized with the blood-brain barrier, and an extra caution is required during procedures that involve engagement of cerebral vessels (i.e., craniotomy). Using state of the art facilities, including 3D intravital microscope, we describe here in details:•The steps and equipment required for drilling a craniotomy and removing of the dura, while keeping brain parenchyma and vessels intact. This enables long duration of live and direct monitoring of pial vessels and imaging of BBB permeability.•We present the craniotomy procedure that relevant and compatible with imaging pial vessels and monitoring the blood-brain barrier in small rodents.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.090
GPT teacher head0.398
Teacher spread0.309 · 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
GenreMethods

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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMethodsXSame topicBarrier Structure and Function StudiesFrench-language works237,207