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Record W1964265171 · doi:10.3791/1259

Dissecting the Non-human Primate Brain in Stereotaxic Space

2009· article· en· W1964265171 on OpenAlexafffund
Mark Burke, Shahin Zangenehpour, Denis Boire, Maurice Ptito

Bibliographic record

VenueJournal of Visualized Experiments · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVervet monkeyPrimateCoronal planeSquirrel monkeyNeuroscienceHuman brainAnatomyBiologyZoology

Abstract

fetched live from OpenAlex

The use of non-human primates provides an excellent translational model for our understanding of developmental and aging processes in humans(1-6). In addition, the use of non-human primates has recently afforded the opportunity to naturally model complex psychiatric disorders such as alcohol abuse(7). Here we describe a technique for blocking the brain in the coronal plane of the vervet monkey (Chlorocebus aethiops sabeus) in the intact skull in stereotaxic space. The method described here provides a standard plane of section between blocks and subjects and minimizes partial sections between blocks. Sectioning a block of tissue in the coronal plane also facilitates the delineation of an area of interest. This method provides manageable sized blocks since a single hemisphere of the vervet monkey yields more than 1200 sections when slicing at 50 microm. Furthermore by blocking the brain into 1cm blocks, it facilitates penetration of sucrose for cyroprotection and allows the block to be sliced on a standard cryostat.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.428

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 science0.0010.000
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 head0.079
GPT teacher head0.546
Teacher spread0.466 · 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.

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

Citations14
Published2009
Admission routes2
Has abstractyes

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