Using Google Trends to investigate global COPD awareness
Bibliographic record
Abstract
We read the recent article published in the European Respiratory Journal by Boehm et al. [1] with great interest: their study is the first to explore global chronic obstructive pulmonary disease (COPD) awareness using Google searches. Currently, with the development of the internet and search engines, Google Trends has emerged as a robust tool to investigate the interest of the general population in medical conditions [2–4]. In the study by Boehm et al. [1], it was found that the awareness of COPD in the real world is rising, while it is highly under-represented in the public interest compared with other common conditions. In addition, public interest in seeking COPD information through Google searches presented a seasonal pattern, with peaks in the first and the fourth quarter of the year. These findings may help to improve programmes to guide interventions for COPD and contribute to the development of preventative healthcare for this disease. Google Trends provides new evidence for public interest and seasonal patterns in COPD <http://bit.ly/2xsGbIE>
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 teacher head, 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".