Bibliographic record
Abstract
Anxiety is one of the most prevalent psychiatric disorders in Canada, with 1 in 4 adults meeting the criteria for diagnosis in their lifetime.Although many of the mechanisms involved in the etiology of anxiety are not yet fully known, there are several environmental and genetic factors that have been identified to increase the risk of developing anxiety in later life, including familial history, severe physical or psychological trauma, and early life stress.The current available treatments for anxiety disorders are far from ideal in that they have delayed therapeutic effects, show selective treatment of symptoms, and approximately half of patients do not respond to current treatment options.This outlines the necessity for further research into the biological basis of anxiety disorders in addition to novel therapeutic targets.Recent research has implicated fibroblast growth factor 2 (FGF2) dysregulation in the pathogenesis of depressive disorders, and has shown considerable promise in being an endogenous anxiolytic factor (Salmaso & Vaccarino, 2011).guidance throughout this challenging process.Thank you for giving me the opportunity to delve into an area of neuroscience that I've never experienced before, and being patient with me while I adapted to the rhythm of the lab.I would also like to extend my thanks to the members of my committee, Dr. Alfonso Abizaid, Dr. Hongyu Sun, and Dr. Renate Ysseldyk, who gave their time, intellect, and unique perspectives to contribute to this project.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.007 | 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".