The Variable Neighborhood Search Metaheuristic for Fuzzy Clustering cDNA Microarray Gene Expression Data
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
Several thousand genes can be monitored simultaneously using cDNA microarray technology. To exploit the huge amount of information contained in gene expression data, adaptation of existing and development of new computational methods are required. Recently, the Fuzzy C-Means (F-CM) method has been applied to cluster cDNA microarray data sets. To overcome some shortcomings of F-CM and to improve its performance, it was embedded into a variable neighborhood search (VNS) metaheuristic. The methodology was used to cluster four cDNA microarray data sets. Results show that VNS+F-CM substantially improves the findings obtained by F-CM. This methodology may yield significant benefit in the improvement of decision support systems used for gene expression classification.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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