Facebook endodontic groups as potential tools to provide learning opportunities
Bibliographic record
Abstract
Online media is one of the educational methods that suits well to the Gen Z's preferred learning styles. 1 Social networking sites are not only predominant in current dental students' social life, but are interlinked with their self-learning, search engines, and brainstorming.Albeit several risks exist upon using social media in learning (for instance, dissemination of inaccurate information, violation of privacy, the possibility to ruin one's reputation, and cyberbullying) 2 ; Facebook groups were considered tools to provide learning opportunities in higher education.3 We hypothesized that this could also be true for dentistryendodontics.The problem is that there is a scarcity of information on social media within the dental education literature, 2 and a paucity of data on content, dynamics, and potential learning opportunities provided by social media endodontic study groups. SOLUTIONAiming to have preliminary information on the potential learning opportunities provided by Facebook endodontic
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".