Bibliographic record
Abstract
matter volume in the left anterior cingulate cortex in 66 Italian patients with schizophrenia, and greater grey matter volume in the left anterior cingulate cortex in 37 Italian controls.In terms of providing evidence that the CNNM2 variant would contribute to social cognition and its neural underpinnings, it is a very interesting study.However, the study has a very important limitation.The reported risk allele was incorrect: the risk allele at rs7914558 is not minor 'A' but major 'G'.Therefore, interpretation of these associations was opposite.At almost the same time, we reported that the rs7914558 variant was associated with grey matter volume in the orbital region of the bilateral inferior frontal gyri in 173 Japanese patients with schizophrenia and 449 healthy individuals.4 Those with the risk G/G genotype of rs7914558 had reduced grey matter volume in the bilateral inferior frontal gyri compared with carriers of the non-risk A allele.Interestingly, the orbital region of the inferior frontal gyrus also plays an important role in social functioning.Taken together, the variant was associated with reduced grey matter volume in putative social cognition-related regions, including the temporal pole, anterior cingulate and inferior frontal cortices, which were reduced in patients with schizophrenia, although the detailed regions were not consistent among the different populations studied.Furthermore, a recent study has indicated that mutations in the CNNM2 gene are associated with intellectual disability, and the knockdown of Cnnm2 isoforms in zebrafish has resulted in disturbed brain development.5 These findings suggest that the CNNM2 variant might play a role in the social cognition and social functioning impairments noted in patients with schizophrenia through the volumetric vulnerability of these grey matter regions.
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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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.053 | 0.027 |
| Insufficient payload (model declined to judge) | 0.019 | 0.011 |
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".