Differentiating Grades of Microglial Activation with Fractal Analysis
Bibliographic record
Abstract
Microglia affect and are sensitive to events in the central nervous system , changing in morphology and function as they respond to and resolve disruptions. Monitoring microglia is, therefore, an important goal of neuroscience. We investigated morphological changes in cultured mouse microglia, using the box counting fractal dimension (DB), lacunarity (Λ), and other measures. The DB and Λ corresponded well to visually applied classification systems of these cells. Complementing such systems, which depend on grossly visible differences between cells, the DB also differentiated between visually indistinguishable microglia in different functional states (i.e., deramifying versus reramifying). The results suggest that fractal analysis may help determine if a microglial cell is “resting”, rousing itself for action, acting subtly, or returning to a resting state. Because of the awesome potential microglia have to affect events in the central nervous system, the implications of this for the study of human health and disease are profound.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".