Trial watch: intratumoral immunotherapy
Bibliographic record
Abstract
While chemotherapy and radiotherapy remain the first-line approaches for the management of most unresectable tumors, immunotherapy has emerged in the past two decades as a game-changing treatment, notably with the clinical success of immune checkpoint inhibitors. Immunotherapies aim at (re)activating anticancer immune responses which occur in two main steps: (1) the activation and expansion of tumor-specific T cells following cross-presentation of tumor antigens by specialized myeloid cells (priming phase); and (2) the immunological clearance of malignant cells by these antitumor T lymphocytes (effector phase). Therapeutic vaccines, adjuvants, monoclonal antibodies, cytokines, immunogenic cell death-inducing agents including oncolytic viruses, anthracycline-based chemotherapy and radiotherapy, as well as adoptive cell transfer, all act at different levels of this cascade to (re)instate cancer immunosurveillance. Intratumoral delivery of these immunotherapeutics is being tested in clinical trials to promote superior antitumor immune activity in the context of limited systemic toxicity.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.111 | 0.023 |
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".