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A collaborative resource platform for non-human primate neuroimaging

2020· article· en· W3099783891 on OpenAlexaff
Adam Messinger, Nikoloz Sirmpilatze, Katja Heuer, Kep Kee Loh, Rogier B. Mars, Julien Sein, Ting Xu, Daniel Glen, Benjamin Jung, Jakob Seidlitz, Paul A. Taylor, Roberto Toro, Eduardo A. Garza‐Villarreal, Caleb Sponheim, Xindi Wang, R. Austin Benn, Bastien Cagna, Rakshit Dadarwal, HC Evrard, Pamela García-Saldivar, Steven Giavasis, Renée Hartig, Claude Lepage, Cirong Liu, Piotr Majka, Hugo Merchant, Michael P. Milham, Marcello G. P. Rosa, Jordy Tasserie, Lynn Uhrig, Daniel S. Margulies, P. Christiaan Klink

Bibliographic record

VenueNeuroImage · 2020
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMontreal Neurological Institute and Hospital
FundersNational Institute of Mental HealthDirectorate for Biological SciencesBiotechnology and Biological Sciences Research CouncilFondation de FranceFondation pour la Recherche MédicaleNational Institutes of HealthAgence Nationale de la RechercheWellcome Trust
KeywordsNeuroimagingField (mathematics)Resource (disambiguation)Computer sciencePrime (order theory)Data scienceNon human primatePsychologyNeuroscienceKnowledge managementBiology

Abstract

fetched live from OpenAlex

Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field .

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)0.000
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
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 score0.413
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.052
GPT teacher head0.320
Teacher spread0.268 · 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.

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

Citations57
Published2020
Admission routes1
Has abstractyes

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