<scp>Competency‐Based</scp> Assessment Tool for Pediatric Esophagoscopy: International Modified Delphi Consensus
Bibliographic record
Abstract
Objectives/Hypothesis Create a competency‐based assessment tool for pediatric esophagoscopy with foreign body removal. Study Design Blinded modified Delphi consensus process. Setting Tertiary care center. Methods A list of 25 potential items was sent via the Research Electronic Data Capture database to 66 expert surgeons who perform pediatric esophagoscopy. In the first round, items were rated as “keep” or “remove” and comments were incorporated. In the second round, experts rated the importance of each item on a seven‐point Likert scale. Consensus was determined with a goal of 7 to 25 final items. Results The response rate was 38/64 (59.4%) in the first round and returned questionnaires were 100% complete. Experts wanted to “keep” all items and 172 comments were incorporated. Twenty‐four task‐specific and 7 previously‐validated global rating items were distributed in the second round, and the response rate was 53/64 (82.8%) with questionnaires returned 97.5% complete. Of the task‐specific items, 9 reached consensus, 7 were near consensus, and 8 did not achieve consensus. For global rating items that were previously validated, 6 reached consensus and 1 was near consensus. Conclusions It is possible to reach consensus about the important steps involved in rigid esophagoscopy with foreign body removal using a modified Delphi consensus technique. These items can now be considered when evaluating trainees during this procedure. This tool may allow trainees to focus on important steps of the procedure and help training programs standardize how trainees are evaluated. Level of Evidence 5. Laryngoscope , 131:1168–1174, 2021
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 | 0.000 | 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 | 0.000 |
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".