Bibliographic record
Abstract
The serotonergic system regulates numerous behaviours and disruptions in this system have been associated with disorders of mood and mind. Although molecular genetic\nanalysis has dissected many of the genes involved in the specification of the serotonergic system, relatively little is known about the mechanisms that promote axonal outgrowth from serotonin-producing neurons and how these projections are directed to innervate and form synapses with their appropriate targets. The mouse\nanorexia mutation causes hypersprouting of serotonergic projections in target fields and has provided us the unique opportunity to examine the crucial events that lead to the establishment of these complex serotonergic networks. Through positional cloning, I have identified a candidate gene that is upregulated during a time in which innervation and synaptogenesis of serotonergic neurons are maximal. I have assessed the expression of this candidate gene in the brain and have found striking differences in the pattern of expression between the normal and the mutant mouse. Furthermore, by using transgenic methods, I have partially rescued several hallmark behavioural phenotypes in the mutant mouse. Thus, this candidate almost certainly represents the\n“Anorexia” gene.
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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 | 0.001 | 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) | 0.005 | 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".