Correction: Altered dynamic functional network connectivity patterns in Alzheimer's disease: insights into neural dysfunction
Bibliographic record
Abstract
Correction: 《Altered dynamic functional network connectivity patterns in Alzheimer's disease: insights into neural dysfunction》 Correction on: Error in figure/table Wrong content There was a mistake in table 1 as published. The female data of the "Gender" column in AD patients was displayed as "28". The corrected table 1 appears below. Table 1. Demographic and clinical data Variables AD patients (n=100) Healthy controls(n=69) Statistics p Demographic factors Age(years) 65.37±9.56 63.45±7.33 t=1.48 0.142 Gender(male/female) 48/52 28/41 x2=0.91 0.341 Education(years) 7.98±4.78 8.42±4.47 t=-0.60 0.550 Psychiatric symptom NPI-12 8.02±11.45 1.96±5.14 t=4.60 0.000** General cognitive performance MMSE 19.20±4.97 28.50±1.60 t=-14.99 0.000** MoCA 13.32±5.60 24.26±3.93 t=-14.93 0.000** Memory performance CAVLT-Immediate 3.42±2.04 8.49±1.92 t=16.01 0.000** CAVLT-Delay 1.33±2.50 9.30±2.82 t=18.59 0.000** 3 CAVLT-Recognition 10.70±4.14 14.15±1.06 t=-6.73 0.000** Language performance VFT 9.66±4.10 17.46±4.03 t=-12.18 0.000** Attention performance DS-Forward 5.79±1.41 6.86±1.42 t=-4.83 0.000** DS-Backward 3.24±1.20 4.07±1.13 t=-4.54 0.000** Visual-spatial performance CDT 1.73±1.25 3.38±1.00 t=-9.47 0.000** AD: Alzheimer's disease; NPI-12:Neuropsychiatric Inventory-12; MMSE: Mini-Mental State Examination; MoCA: Montreal Cognitive Assessment; CAVLT: Chinese version of the Auditory Verbal Learning Test; VFT: Verbal Fluency Test; DS: Digit Span Test; CDT: Clock Drawing Test. **p<0.01.
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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 | 0.091 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.156 | 0.063 |
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".