Management of the Injured Patient: Identification of Research Topics for Systematic Review Using the Delphi Technique
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: Systematic reviews of controlled clinical trials in the form of meta-analyses can serve as an important guide to direct clinical practice. This study identifies the most important research questions pertaining to the acute care of the injured patient using a Web-based Delphi technique to achieve consensus of expert opinion. METHODS: Experts in trauma care from the United States and Canada (n = 68) were asked to generate structured research questions and were then required to rank these questions in order of importance and estimate the amount of research currently published. RESULTS: The questions ranking in the highest tertile are presented along with an estimate of their importance and the amount of research published using an ordinal scale. Only 9 of 16 (56%) questions had some or a substantial amount of research available on which to perform a systematic review. CONCLUSION: This study identifies the areas of trauma care in which research efforts might best be directed. In the absence of sufficient data for systematic reviews, these research topics represent important areas for the design and implementation of clinical trials.
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.
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 | 0.002 | 0.001 |
| 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 it