Bibliographic record
Abstract
A new Guinness World Record was set on World Mental Health Day (Oct. 10) when more than 1,400 participants joined a global video call focused on mental health awareness. The event, led by Hull College in Hull, England, united staff, students, and employees from companies including Smith+Nephew, Think Cloud and Think Mental Health, BBC News reported Oct. 14. The initiative aimed to break the stigma around discussing mental health and succeeded in setting the record for the most users in a mental health awareness video lesson, with 916 verified attendees and over 1,400 participants at its peak — surpassing the previous record of 770. Participants joined from across the globe, including the United States, Canada, Mexico, Costa Rica, India, Italy, Germany, China and several other countries. Hull College Principal Debra Gray called the achievement “a testament to what can be achieved when education, business, and the community come together with a shared purpose.” Organizers described the event as a “shared moment of reflection, learning, and conversation.”
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.185 | 0.093 |
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".