ENU‐3 functions in an UNC‐6/netrin dependent pathway parallel to UNC‐40/DCC/frazzled for outgrowth and guidance of the touch receptor neurons in<i>C. elegans</i>
Bibliographic record
Abstract
BACKGROUND: UNC-6 and SLT-1 guide the migrations of the ventrally directed processes of the AVM and PVM touch receptor neurons and UNC-6 guides the axons of the DA and DB classes of motor neurons in C. elegans. The UNC-6 receptors are UNC-5 and UNC-40. The axon outgrowth defects of a subset of the DB motor neurons in the absence of UNC-5 are enhanced by mutations in enu-3. RESULTS: An enu-3 mutation enhances defects in ventral guidance of the processes of the AVM and PVM touch receptor neurons, the dorsal guidance of the distal tip cell and causes additional architectural defects in axons in unc-40 mutant strains in an UNC-6 dependent manner. These observations suggest that ENU-3 and UNC-40 function in parallel pathways dependent on UNC-6. ENU-3 depends on the presence of UNC-40 for its full effect on motor neuron axon outgrowth. CONCLUSIONS: ENU-3 works in an UNC-6 dependent pathway parallel to UNC-40 in ventral guidance of AVM and PVM and in dorsal guidance of the distal tip cells. Motor neuron axon outgrowth defects are caused by the presence of UNC-40 and the absence of functional UNC-5 or UNC-6 and defects are enhanced by the absence of functional ENU-3.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".