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Record W4253325890 · doi:10.35430/nab.2021.e27

How we are building Neuroanatomy and Behaviour for rigorous andopen science

2021· article· en· W4253325890 on OpenAlexafffund
Shaun Yon‐Seng Khoo

Bibliographic record

VenueNeuroanatomy and Behaviour · 2021
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec - Santé
KeywordsOpen scienceMilestoneComputer scienceDirectoryData scienceKey (lock)World Wide WebPsychology

Abstract

fetched live from OpenAlex

Neuroanatomy and Behaviour was founded to be a journal for rigorous and open science. In 2021, all of the empirical papers published engaged in at least one open science practice, such as open data or open protocols. The papers published have been carefully reviewed by two experts, but may also be sent to additional specialist reviewers for specific tasks, such as checking references or statistical approaches. In 2021, Neuroanatomy and Behaviour reached a key milestone and was accepted into the Directory of Open Access Journals, the world’s leading database of trustworthy open access journals. As we look towards 2022, we will continue improving our publication processes and working to share quality neuroscience without financial barriers for authors or readers.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.036
GPT teacher head0.286
Teacher spread0.250 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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