MétaCan
Menu
Back to cohort
Record W2509773387 · doi:10.1364/boe.7.003596

Imaging brain activity during seizures in freely behaving rats using a miniature multi-modal imaging system

2016· article· en· W2509773387 on OpenAlexafffund
Iliya Sigal, Margaret M. Koletar, Dene Ringuette, Raanan Gad, Melanie Jeffrey, Peter L. Carlen, Bojana Stefanovic, Ofer Levi

Bibliographic record

VenueBiomedical Optics Express · 2016
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsSunnybrook Health Science CentreKrembil FoundationUniversity of Toronto
FundersCanadian Institutes of Health ResearchConnaught FundNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsNeuroimagingCraniotomyMedicineNeurovascular bundleBlood oxygenationBiomedical engineeringBlood flowFunctional imagingCerebral blood flowRadiologyAnesthesiaPathology

Abstract

fetched live from OpenAlex

We report on a miniature label-free imaging system for monitoring brain blood flow and blood oxygenation changes in awake, freely behaving rats. The device, weighing 15 grams, enables imaging in a ∼ 2 × 2 mm field of view with 4.4 μm lateral resolution and 1 - 8 Hz temporal sampling rate. The imaging is performed through a chronically-implanted cranial window that remains optically clear between 2 to > 6 weeks after the craniotomy. This imaging method is well suited for longitudinal studies of chronic models of brain diseases and disorders. In this work, it is applied to monitoring neurovascular coupling during drug-induced absence-like seizures 6 weeks following the craniotomy.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.017
GPT teacher head0.319
Teacher spread0.302 · 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
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

Citations25
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueBiomedical Optics ExpressSame topicOptical Imaging and Spectroscopy TechniquesFrench-language works237,207