Bibliographic record
Abstract
Pseudomyxoma peritonei (PMP) is a mucinous tumour of the appendix that spreads into the peritoneal cavity in the form of gelatinous deposits. The incidence of PMP is believed to be approximately 1-3 out of a million per year. Nonetheless, due to its indolent nature, it is usually discovered at an advanced stage and severely impacts quality of life. Curative treatment for PMP is complete cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC). An extensive literature review was conducted searching EMBASE, MEDLINE, PubMed, and Google Scholar databases for PMP in aims to delineate a clinical approach to diagnosis and treatment. Literature was limited to the years 2007-2018. We found the 5-year overall survival with CRS and HIPEC estimated to be between 23%-82% and rates of major complications as high as 24%. Therefore, it is important to appropriately stage and select patients that should undergo CRS with HIPEC. Modalities like MDCT radiological scores have been shown to have sensitivity and specificity of 94% and 81%, respectively, in being able to predict resectability and survival. Despite treatment, the disease often recurs. Tumor markers have significant potential for establishing prognosis pre-operatively, and this paper will review the most recent evidence in support of them.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".