Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to compare the proposed complication severity score (CSS) with comprehensive complication index (CCI) using a questionnaire-based survey of experienced gastrointestinal and hepato-pancreatico-biliary surgeons. BACKGROUND: Morbidity rate has become an important outcome measure, as the mortality rates of most surgical procedures have decreased substantially. The recently developed CCI for measuring complications is a step forward in this process but has some drawbacks. We developed a new scoring system for calculating morbidity and compared it with CCI. METHODS: We designed a questionnaire with 9 scenarios wherein each scenario compared a hypothetical patient who developed a number of lower grade complications with another hypothetical patient who underwent the same surgical procedure but developed a single higher grade complication. The questionnaire was sent to 50 experienced surgeons who were asked to choose the patient who in their opinion had more severe complication. The results thus obtained were compared with the CSS and the CCI for these patients. RESULTS: Forty-nine of fifty experienced surgeons replied. Of the 9 sets of scenarios, experienced surgeons' opinion matched with CSS alone in six, CSS as well as CCI in one, and neither CSS or CCI in two scenarios. Of the total 441 responses, 281 matched with CSS while 143 matched with CCI (P = 0.0001, odds ratio: 3.7; 95% CI 2.8-4.8). CONCLUSIONS: CCI was not accurate in calculating the severity of a combination of postoperative complications. The CSS more often matched the opinion of experienced senior surgeons but requires further modifications.
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 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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.516 | 0.370 |
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".