Cancer vaccines: past, present and future; a review article
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Immunotherapy and vaccines have revolutionized disease treatment and prevention. Vaccines against infectious diseases have been in use for several decades. In contrast, only few cancer vaccines have been approved for human use. These include preventative vaccines against infectious agents associated with cancers, and therapeutic vaccines used as immunotherapy agents to treat cancers. Challenges in developing cancer vaccines include heterogeneity within and between cancer types, screening and identification of appropriate tumour-specific antigens, and the choice of vaccine delivery platforms. Recent advances in all of these areas and the lessons learnt from COVID-19 vaccines have significantly boosted interest in cancer vaccines. Further advances in these areas are expected to facilitate development of effective novel cancer vaccines. In this review, we aim to discuss the past, the present, and the future of cancer vaccines.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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 it