Next Generation Vaccine Biomarkers workshop October 30–31, 2014 – Ottawa, Canada
Bibliographic record
Abstract
Vaccine biomarkers are critical to many aspects of vaccine development and licensure, including bridging findings in pre-clinical studies to clinical studies, predicting potential adverse events, and predicting vaccine efficacy. Despite advances in our understanding of various biological pathways, and advances in systems analyses of the immune response, there remains much to learn about qualitative and quantitative aspects of the human host response to vaccination. To stimulate discussion and identify opportunities for collaborative ways to advance the field of vaccine biomarkers, A Next Generation Vaccine Biomarker workshop was held in Ottawa. The two day workshop, sponsored by the National Research Council Canada, Canadian Institutes of Health Research, Public Health Agency of Canada, Pfizer, and Medicago, brought together stakeholders from Canadian and international industry, government and academia. The workshop was grouped in themes, covering vaccine biomarker challenges in the pre-clinical and clinical spaces, veterinary vaccines, regulatory challenges, and development of biomarkers for adjuvants and cancer vaccines. The use of case studies allowed participants to identify the needs and gaps requiring innovation. The workshop concluded with a discussion on opportunities for vaccine biomarker discovery, the Canadian context, and approaches for moving forward. This article provides a synopsis of these discussions and identifies steps forward for advancing vaccine biomarker research in Canada.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".