Bibliographic record
Abstract
Abstract The cerebellum is a highly stereotyped cortical structure in the hindbrain of all vertebrates from fish to primates. The circuitry of the cerebellar cortex is built around the large, inhibitory Purkinje cells, which are the focus of all afferent input to the cerebellar cortex and are modulated by several classes of inhibitory interneuron (principally basket, stellate, and Golgi cells). Despite the apparent homogeneity of the cerebellar circuitry, the cerebellum is highly modular, comprising several hundred discrete and reproducible anatomical and physiological units (‘stripes’). Each stripe receives precise afferent inputs – climbing fibres directly to the Purkinje cells and mossy fibres indirectly via the granule cells. In turn, the Purkinje cells send efferent projections to specific targets in the cerebellar and vestibular nuclei. As a result, within the cerebellum a wide variety of sensory information is brought together and integrated, primarily to aid in motor control but also serving multiple other functions. Key Concepts Cerebellar circuitry is built around the Purkinje cell. The cerebellar cortex is divided into an array of transverse zones and parasagittal stripes. The cerebellar cortex receives two major afferent inputs – climbing fibres and mossy fibres. Purkinje cells are the sole efferent projections of the cerebellar cortex. Multiple interneurons modulate Purkinje cell firing patterns.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".