Extraction and distribution of vascular mild cognitive impairment syndrome factors based on factor analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective:To explore the syndrome factors distribution for vascular mild cognitive impairment,in order to provide the evidence for the standardization of syndrome differentation.Methods:803 cases of vascular mild cognitive impairment were selected from multi-centers.Factor analysis was used to find out the common syndrome factors.Then,the distribution of syndrome factors was summary.Results:The distribution of the 6 syndrome factors were:patients with qi deficiency up to 25.90%, followed by blood stasis(18.31%),phlegm(16.94%),yin deficiency(14.32%),yang deficiency(13.57%),fire(10.96%).The main involved organs were the kidney and liver,followed by the heart and spleen.Patients with higher MoCA score manifested commonly as qi deficiency,phlegm,blood stasis.Patients with lower MoCA score manifested commonly as qi deficiency,yang deficiency,blood stasis.There was positively correlation between the number of damaged cognitive function sub-items and qi deficiency score,and the correlation coefficient was 0.135(P0.01).Conclusion:The syndrome factors of take deficiency as root cause and blood stasis,phlegm camee as symptoms cause and evolved with the progress of the.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it