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Record W4409152763 · doi:10.1038/s41593-025-01907-4

Human lifespan changes in the brain’s functional connectome

2025· article· en· W4409152763 on OpenAlexaff
Lianglong Sun, Tengda Zhao, Xinyuan Liang, Mingrui Xia, Qiongling Li, Xuhong Liao, Gaolang Gong, Qian Wang, Chenxuan Pang, Qian Yu, Yanchao Bi, Pindong Chen, Rui Chen, Yuan Chen, Jingliang Cheng, Yuqi Cheng, Zaixu Cui, Zhengjia Dai, Yao Deng, Yuyin Ding, Qi Dong, Dingna Duan, Jia‐Hong Gao, Qiyong Gong, Ying Han, Zaizhu Han, Chu‐Chung Huang, Ruiwang Huang, Ran Huo, Lingjiang Li, Ching‐Po Lin, Qixiang Lin, Bangshan Liu, Chao Liu, Ningyu Liu, Ying Liu, Yong Liu, Jing Lu, Leilei Ma, Weiwei Men, Shaozheng Qin, Jiang Qiu, Shijun Qiu, Tianmei Si, Shuping Tan, Yanqing Tang, Sha Tao, Dawei Wang, Fei Wang, Jiali Wang, Pan Wang, Xiaoqin Wang, Yanpei Wang, Dongtao Wei, Yankun Wu, Peng Xie, Xiufeng Xu, Yuehua Xu, Zhilei Xu, Liyuan Yang, Huishu Yuan, Zilong Zeng, Haibo Zhang, Xi Zhang, Gai Zhao, Yanting Zheng, Suyu Zhong

Bibliographic record

VenueNature Neuroscience · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsSt Joseph's Health CareSt Joseph's Health CentreUniversity of British ColumbiaSunnybrook Health Science CentreJewish General Hospital
FundersNational Institute on AgingChangjiang Scholar Program of Chinese Ministry of EducationNational Natural Science Foundation of China
KeywordsNeuroscienceConnectomeNeuroscientistFunctional connectivityHuman brainPsychologyNerve netBiologyCentral nervous system

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.039
GPT teacher head0.310
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations94
Published2025
Admission routes1
Has abstractno

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