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Record W2335271347 · doi:10.1186/s13742-016-0121-x

Brainhack: a collaborative workshop for the open neuroscience community

2016· review· en· W2335271347 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGigaScience · 2016
Typereview
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsBaycrest HospitalOntario Institute for Cancer ResearchMcGill UniversityUniversity of TorontoUniversity Health NetworkMontreal Neurological Institute and HospitalUniversité de MontréalPolytechnique MontréalInstitut Universitaire de Gériatrie de Montréal
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute on Alcohol Abuse and AlcoholismCentre d'Imagerie BioMédicaleWellcome TrustAgence Nationale de la RechercheChild Mind InstituteRéseau en Bio-Imagerie du QuebecWellcomeOntario Brain InstituteMicrosoft AzureNational Institutes of HealthAmazon Web ServicesFrontiers Clinical and Translational Science Institute, University of KansasAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital
KeywordsOpen scienceComputer scienceData scienceNeuroscienceWorld Wide WebCognitive sciencePsychology

Abstract

fetched live from OpenAlex

Brainhack events offer a novel workshop format with participant-generated content that caters to the rapidly growing open neuroscience community. Including components from hackathons and unconferences, as well as parallel educational sessions, Brainhack fosters novel collaborations around the interests of its attendees. Here we provide an overview of its structure, past events, and example projects. Additionally, we outline current innovations such as regional events and post-conference publications. Through introducing Brainhack to the wider neuroscience community, we hope to provide a unique conference format that promotes the features of collaborative, open science.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.526

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 science0.0030.000
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 head0.116
GPT teacher head0.380
Teacher spread0.265 · 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