The Virtual Face of Colon and Rectal Surgery Training in the USA: An In‐Depth Evaluation and Analysis of Fellowship Programs Website Content
Bibliographic record
Abstract
BACKGROUND: With an ever-evolving digital and virtual world hastened by the COVID-19 pandemic, prospective colon and rectal surgery fellowship applicants must rely on online sources of information, such as websites, rather than in-person visits to fellowship programs. This study analyzes and evaluates the content and accuracy of colon and rectal surgery fellowship program websites. METHODS: The Fellowship and Residency Electronic and Interactive Database website provides a complete collection of colon and rectal surgery fellowship websites based in the USA. The accessibility of the websites was verified via Google search, and relevant content for the applicants was evaluated based on 50-point criteria. RESULTS: Analysis of 60 fellowship program websites was conducted, out of which only a fifth (20%) were kept up to date. Twenty-seven (45%) websites fulfilled 50% of the 50-point criteria. The most and least included data points were program overview (69%) and residential/housing information (24%). Most websites contained basic information relevant to international applicants but lacked crucial information such as visa sponsorship (12%) and city information (23%). CONCLUSION: An informative and easily accessible website is essential for prospective applicants to choose the best program for their career goals and academic needs. This study highlighted multiple areas for potential improvement in the colon and rectal surgery program websites. Individual colon and rectal surgery programs may benefit and attract more candidates to their programs through a fully optimized website design and content.
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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 | 0.025 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".