"Association of the K-RAS Gene Mutation with Gallbladder Cancer"
Bibliographic record
Abstract
The early development of gallbladder cancer is usually asymptomatic and has a high tendency to metastatic spread, so most patients are diagnosed in intermediate to advanced stages.The role of various genetic mutations is a currently active field of research that has sometimes transformed the diagnosis and/or treatment of some types of cancer.The point mutation in codon 12 of the K-ras gene has become the target of analysis in different studies, because there is considerable debate about the frequent presence of this mutation in malignant lesions of the gallbladder.Therefore, demonstrating whether there is a significant association through an analytical study could be useful to offer a useful molecular diagnostic marker in the detection of the early stage of carcinogenesis in the gallbladder and reduce a public health problem.This meta-analysis was performed through a systematic search using the PubMed and EBSCO library databases, where 10 studies with a total of 221 cases and 163 controls were selected.Publication bias was assessed using the GRADE approach and the quality of each study was assessed independently using the Newcastle-Ottawa Assessment Scale.Epi-data version 3.1 software was used to assess this association, where our results demonstrated a significant association between the mutation of codon 12 of the K-ras gene and the risk of gallbladder cancer (OR: 0.18; IC 95%: 0.08-0.41).The P value of the Q test was: 0.32.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.019 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".