The evolution of the axonal transport toolkit
Bibliographic record
Abstract
Neurons are highly polarized cells that critically depend on long-range, bidirectional transport between the cell body and synapse for their function. This continual and highly coordinated trafficking process, which takes place via the axon, has fascinated researchers since the early 20th century. Ramon y Cajal first proposed the existence of axonal trafficking of biological material after observing that dissociation of the axon from the cell body led to neuronal degeneration. Since these first indirect observations, the field has come a long way in its understanding of this fundamental process. However, these advances in our knowledge have been aided by breakthroughs in other scientific disciplines, as well as the parallel development of novel tools, techniques and model systems. In this review, we summarize the evolution of tools used to study axonal transport and discuss how their deployment has refined our understanding of this process. We also highlight innovative tools currently being developed and how their addition to the available axonal transport toolkit might help to address key outstanding questions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".