The Cuban Human Brain Mapping Project population based normative EEG, MRI, and Cognition dataset
Bibliographic record
Abstract
Abstract The Cuban Human Brain Mapping Project (CHBMP) repository is an open multimodal neuroimaging and cognitive dataset from 282 healthy participants (31.9 ± 9.3 years, age range 18–68 years). This dataset was acquired from 2004 to 2008 as a subset of a larger stratified random sample of 2,019 participants from La Lisa municipality in La Habana, Cuba. The exclusion included presence of disease or brain dysfunctions. The information made available for all participants comprises: high-density (64-120 channels) resting state electroencephalograms (EEG), magnetic resonance images (MRI), psychological tests (MMSE, Wechsler Adult Intelligence Scale -WAIS III, computerized reaction time tests using a go no-go paradigm), as well as general information (age, gender, education, ethnicity, handedness and weight). The EEG data contains recordings with at least 30 minutes duration including the following conditions: eyes closed, eyes open, hyperventilation and subsequent recovery. The MRI consisted in anatomical T1 and T2 as well as diffusion weighted (DWI) images acquired on a 1.5 Tesla system. The data is available for registered users on the LORIS database which is part of the MNI neuroinformatics ecosystem.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".