Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Beta-blockers (β-blockers) are pharmacotherapeutics that have been used to treat patients with cardiovascular symptoms since their discovery in the 1960s. They work by targeting B1 and B2 receptors which are involved the stress response, which consequently lead to reduced activation of the “flight-or-fight mechanism”. It has also been noticed that β-blockers can be beneficial in treating anxiety disorders and other mental health complications. Currently, the only approved drugs for anxiety and other mental health conditions include benzodiazepines and selective serotonin reuptake inhibitors. Historically, there has been strong resistance to the use of β-blockers in mental health treatment because of the prevalence of depressive symptoms during treatment. Recently, a growing number of studies have seen that there is no strong relationship between β-blockers and depression in patients. Although there are still other adverse effects related to the usage of β-blockers, investigating the relationship between depressive symptoms and β-blockers may suggest a potential therapeutic option in mental health treatments. This review explores the history of β-blockers, their mechanism of action, developments in their use as a mental health treatment and current approved pharmacotherapeutics for mental health. 
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it