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
Microglia, the tissue-resident macrophages of the central nervous system (CNS), have characterized roles in combating infection, clearing cellular debris, and maintaining tissue homeostasis. In addition to these typical immunological roles, microglia have been revealed to be active players in complex neurodevelopmental programs such as neurogenesis and synaptic pruning, during which they interact with neurons and macroglia to provide trophic support, respond to cytokine, and metabolic signals derived from the local neural environment, and drive the refinement of functional neuronal circuits. Microglia appear to be developmentally regulated by the host microbiome, and have been shown to dynamically respond to metabolic products from gut microbiota in a sex-dependent manner. Due to their constant surveillance of the brain parenchyma, involvement in development, and salient reactivity to both peripheral immune and microbiome-derived signals, microglia may additionally serve as a key cellular intermediate linking neurodevelopmental disorders such as autism and schizophrenia with microbiota influences in models of maternal immune activation (MIA). This review examines both well-established and emerging literature and perspectives on microglia in the context of neurodevelopment, with a particular emphasis on the role of the host microbiome in influencing microglial function during health and disease states.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.006 | 0.002 |
| 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