Data for Tract-based Fractional Anisotropy predicts WAIS Intelligence Quotient indices and subtest performance
Bibliographic record
Abstract
The sample included 83 healthy right-handed participants who are part of the Cuban Project of Human Brain Mapping with an average age of 35.06 ± 10.21 years and 12.12 ± 2.46 years of education. The recruitment was based on a completely randomized sampling using the identity card database stratified by age, gender and outward ethnic features of 2,109 subjects of the whole population of La Lisa municipality (more than 30,000) in La Habana. It’s important to note that this municipality was selected because closely matched the general statistics of the Cuban population according to the national census of the republic of Cuba http://www.one.cu/. The present study was carried out in accordance with The Code of Ethics of the World Medical Association, Declaration of Helsinki (W.M., 1996), and the experimental protocols were approved by the Ethics Committee of the Cuban Neuroscience Center. The recruitment procedure did not involve any kind of reward but only feedback about the results and participants were included in the study after accepting and signing the informed consent . A multiple ROIs approach was used for the reconstruction of the tracts of interest because it has been shown that the two-ROI and brute-force approach could effectively reduce the sensitivity to the noise and ROI placement (Huang, Zhang, van Zijl, & Mori, 2004). The fiber tracking was performed on all voxels of the brain, and fibers that penetrated the previously defined ROIs were assigned to the specific tracts associated with each pair of ROIs.Definition of ROIs for studied tracts was made by replicating a set of predefined ROI by Mori et al. (2002) that was employed successfully in subsequent work (Góngora, Domínguez, & Bobes, 2016; Hua et al., 2008; Wakana et al., 2007; Wakana et al., 2005; Wakana, Jiang, Nagae-Poetscher, Van Zijl, & Mori, 2004). The following procedure replicated the methodology published by Góngora et al., 2016. These ROIs were drawn using the program MRIcron (http://www.mricron.com) on a reference anatomical image with a spatial resolution of 1 x 1 x 1 mm3 in stereotactic space of the Montreal Neurological Institute (MNI) (Evans et al., 1993). The ROIs were then transformed to each individual brain space automatically, using a programmed routine in Matlab. The ROIs were defined for the following tracts: anterior thalamic radiation (ATR), cingulate gyrus associated cingulum (CGC), hippocampal gyrus associated cingulum (CGH), corticospinal tract (CST), inferior fronto-occipital fasciculus (IFO), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), uncinate fasciculus (UNC), forceps major (Fmj) and forceps minor (Fmn). The resulting path of these tracts was visually inspected and corrected in cases where necessary, by the exclusion of fibers that did not belongs anatomically to tracts. For the statistical analysis we estimate the FA average between the corresponding bilateral tracts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".