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Record W6967842384 · doi:10.5281/zenodo.11126592

Tracking the neurodevelopmental trajectory of beta band oscillations with OPM-MEG

2024· dataset· en· W6967842384 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typedataset
Languageen
FieldArts and Humanities
TopicAncient Egypt and Archaeology
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMagnetoencephalographyTracking (education)TrajectoryTask (project management)Pattern recognition (psychology)Head (geology)Scripting language

Abstract

fetched live from OpenAlex

Optically pumped magnetometer magnetoencephalography (OPM-MEG) data were acquired during a somatosensory task using a 192-channel OPM-MEG device which is adaptable to head size and robust to participant movement. This dataset contains data from individuals aged between 2 and 34 years. Analyses and descriptions of the dataset were published in eLife (https://doi.org/10.7554/eLife.94561.1) Defaced, T1-weighted MR images are provided for each participant. These were generated using an individualized template anatomy approach where age-matched template MRIs were warped to an optical 3D scan of each individual's head-shape. Data were compressed using zip on Windows. Matlab (2022b) scripts used for data loading and analysis can be found on (https://github.com/LukasRier/RierRhodes_2024_Neurodevelopmental_OPMMEG)

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.020

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 head0.045
GPT teacher head0.229
Teacher spread0.184 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicAncient Egypt and ArchaeologyFrench-language works237,207