Predictive value of MEP1A in cancer prognosis
Bibliographic record
Abstract
BACKGROUND: Meprin is a member of the astaxanthin family; it performs many functions through a wide range of proteolytic enzyme activities during health and disease, including tumors and inflammatory conditions. The purpose of this systematic review was to evaluate the predictive value of MEP1A in tumor prognosis. METHODS: A comprehensive search was conducted on PubMed, Cochrane library, and Web of Science Database using a developed search strategy. The Newcastle-Ottawa Scale (NOS) or the Cochrane Collaboration's tool for assessing risk of bias will be used to access the methodological quality of included studies, and GRADE will be applied to evaluate evidence quality of outcomes. All analyses were performed by Stata 15.0. RESULTS: The results will systematically summarize and display the currently collected evidence on the predictive value of MEP1A in different tumor prognosis. CONCLUSION: This study may play a certain role in predicting the prognosis of cancer patients in the future, and may prompt clinicians to make necessary treatment or prevention plans as soon as possible. ETHICS AND COMMUNICATION: It is not necessary because the present systematic review is based on published studies. INPLASY REGISTRATION NUMBER: INPLASY2020100005.
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 | 0.008 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".