Bibliographic record
Abstract
Social media sites are becoming more and more popular within the healthcare industry. There is a huge potential in research for using different social media sites for retention and looking at their long term effects in a longitudinal study like the CHILD study – something not yet looked into at depth [ 1 ]. At present, most social media sites in research are involved in recruiting participants for studies. Social media provides an exploratory and informative environment for families involved in longitudinal studies. Researchers and study families can mutually share information – creating a web of connections through the internet. Such engagement may help in the retention of participants in a longitudinal study. Keep connections with study families in a timely fashion. Facebook is able to show what a research team does on a regular basis. Researchers can share information regarding recent and related publications. Because of the many connections of those signed in to Facebook, communities are built [ 2 ] and users become engaged. Facebook has the ability to poll the public on different issues and gives insights and data to group administration. Keep connections with other health care professionals, researchers and members of the general public. There is a potential for collaboration. Talks directly to experts and “clients” and gives all the ability to connect to each other. Share allergy and asthma news with the public in one area. Pinterest is a collection of links to articles and websites about information surrounding research in pediatric allergy and asthma. The sharing of photos. Researchers can share photos of the lab environment; including how to capture data and measurements. This aids in daily contact with the families of research studies. Benefits the families; allows the kids to see the testing environment and opens up links of communication. The ability to link social media sites to each other offers the availability of information to be accessed in different means, furthering the webs of connection. There are no results yet from the usage of social media for the retentions of a longitudinal cohort like CHILD. With more time and analysis, significant results are anticipated. There are limitations to using social media for a research study. There must be time allocated to updating each site as regularly as possible. The Internet is still not accessible to all despite being accessible to many. Information is only shared with those engaged in social media. In these cases, research studies must find other ways to ensure that the information is equally distributed. With the help of social media, longitudinal research studies are able to keep a presence in the daily lives of participating families. This helps to strengthen connections for the study and may ultimately help in retention. When looking at conducting a study, researchers should not shy away from social media sites.
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 | 0.035 | 0.158 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.018 | 0.041 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".