Gradients and Growth Cone Guidance of Grasshopper Neurons
Bibliographic record
Abstract
The generation of a functional nervous system is dependent on precise pathfinding of axons during development. This pathfinding is directed by the distribution of local and long-range guidance cues, the latter of which are believed to be distributed in gradients. Gradients of guidance cues have been associated with growth cone function for over a hundred years. However, little is known about the mechanisms used by growth cones to respond to these gradients, in part owing to the lack of identifiable gradients in vivo. In the developing grasshopper limb, two gradients of the semaphorin Sema-2a are necessary for correct neuronal pathfinding in vivo. The gradients are found in regions where growth cones make critical steering decisions. Observations of different growth cone behaviors associated with these gradients have provided some insights into how growth cones respond to them. Growth cones appear to respond more faithfully to changes in concentration, rather than absolute levels, of Sema-2a expression, whereas the absolute levels may regulate growth cone size.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".