Can ChatGPT Guide Parents on Tympanostomy Tube Insertion?
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
BACKGROUND: The emergence of ChatGPT, a state-of-the-art language model developed by OpenAI, has introduced a novel avenue for patients to seek medically related information. This technology holds significant promise in terms of accessibility and convenience. However, the use of ChatGPT as a source of accurate information enhancing patient education and engagement requires careful consideration. The objective of this study was to assess the accuracy and reliability of ChatGPT in providing information on the indications and management of complications post-tympanostomy, the most common pediatric procedure in otolaryngology. METHODS: We prompted ChatGPT-3.5 with questions and compared its generated responses with the recommendations provided by the latest American Academy of Otolaryngology-Head and Neck Surgery Foundation (AAO-HNSF) "Clinical Practice Guideline: Tympanostomy Tubes in Children (Update)". RESULTS: A total of 23 responses were generated by ChatGPT against the AAO-HNSF guidelines. Following a thorough review, it was determined that 22/23 (95.7%) responses exhibited a high level of reliability and accuracy, closely aligning with the gold standard. CONCLUSION: Our research study indicates that ChatGPT may be of assistance to parents in search of information regarding tympanostomy tube insertion and its clinical implications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it