Summary statistics of the X-chromosome for 2,822 brain imaging traits in UKB (n = 34,000)
Bibliographic record
Abstract
This deposit hosts X-chromosome association summary statistics using 34,000 UKB white subjects for 2,822 brain imaging traits, including 101 regional brain volume traits, 63 cortical thickness traits, 66 surface area traits, 525 DTI PC traits, 110 DTI tract-mean traits, 1,777 ICA resting-state functional MRI (rfMRI) traits, 90 Glasser360 mean-level rfMRI traits, and 90 Glasser360 mean-level task-evoked functional MRI (trfMRI) traits. The shared data includes: 1. sex-agnostic association analysis for X-chr (PAR and NPR) 2. sex-stratified association analysis for X-chr (PAR and NPR) The corresponding article: Jiang, Zhiwen, et al. "The pivotal role of the X-chromosome in the genetic architecture of the human brain." medRxiv (2023): 2023-08.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".