Bibliographic record
Abstract
This is a retrospective study assessing the accuracy of diagnosis, clinical features and outcome of patients coded with a medical record diagnosis of hepatorenal syndrome (HRS) between 1988 and 1998 in a tertiary care centre in Canada. The authors found that, of the 46 patients whose medical records revealed a diagnosis of HRS, only 27 patients (59%) fulfilled the criteria for the diagnosis of HRS defined by the International Ascites Club (IAC) (1). Most patients with HRS were middle-aged men with decompensated alcoholic cirrhosis, jaundice and hepatic encephalopathy. Infection (48%), gastrointestinal bleeding (33%) and overly aggressive paracentesis (27%) were the major precipitants of renal failure. Once HRS developed, the mortality rate was high (93%), with multiorgan failure being the most common cause of death. The authors concluded that diagnostic accuracy is paramount for studies of HRS. In addition, decompensated alcoholic cirrhosis remains the main predisposing factor for HRS, with various other factors precipitating its development.
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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.009 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".