Fronto‐cerebellar loop and declines in the performance intelligence scale
Bibliographic record
Abstract
In their very interesting study Lee et al. found that the right neocerebellum was significantly associated with scores of the performance intelligence scale while frontal lobes were not.1 Age negatively correlated with left inferior frontal gyrus (Broadmann area 47), left postcentral gyrus (Broadmann area 3), left superior temporal gyrus (Broadmann area 42), right precuneus of parietal lobe (Broadmann area 39), and the posterior lobe of right lateral cerebellum gray matter densities. The authors suggest that the right cerebral hemisphere, which mediates non-verbal performance, is connected to the right cerebellar hemisphere. In our view the right cerebral hemisphere (in particular the prefrontal cortex) is connected via the cerebro–pontine–cerebellar pathway with the left cerebellar hemisphere. In contrast, the left cerebellar hemisphere projects to the left nucleus dentatus and via the right thalamus to the right prefrontal cortex.2 The right cerebellar hemisphere is thus connected with the left prefrontal cortex, where negative correlation with age was observed. The absence of association between the performance intelligence scores and the left frontal gray matter density could indeed be due to methodological issues. The authors mention one source of error: the use of the template acquired from the population not corresponding to studied subjects in pertinent variables, such as age. Job et al. report compatible results for images spatially normalized to both the generic SPM T1 template and the custom made template.3 However, more differences were found using a study-specific template. Another methodological concern is the large cluster size (100 voxels). The selection of the cluster extent is usually arbitrary. The rationale is to reduce the chance of false-positive findings. However, the use of large clusters may lead to false-negative findings.4 Because Lee et al. had apriori hypotheses about the association between the performance intelligence decline in normal aging and the loss of gray matter in frontal cortices,1 the use of smaller cluster might be warranted.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".