Intervening along the spectrum of tuberculosis: meeting report from the World TB Day nanosymposium in the Institute of Infectious Disease and Molecular Medicine at the University of Cape Town
Bibliographic record
Abstract
<ns3:p> Tuberculosis, caused by the highly infectious <ns3:italic>Mycobacterium</ns3:italic> <ns3:italic>tuberculosis</ns3:italic> , remains a leading cause of death worldwide, with an estimated 1.6 million associated deaths reported in 2017. In South Africa, an estimated 322,000 people were infected with TB in 2017, and a quarter of them lost their lives due to the disease. Bacille Calmette-Guérin remains the only effective vaccine against disseminated TB, but its inability to confer complete protection against pulmonary TB in adolescents and adults calls for an urgent need to develop new and better vaccines. There is also a need to identify markers of disease protection and develop novel drugs. On March 25 <ns3:sup>th</ns3:sup> 2019, the Institute of Infectious Disease and Molecular Medicine at the University of Cape Town hosted the second annual World TB Day nanosymposium. The theme of the nanosymposium was “Intervening across the spectrum of TB II” and the goal was to commemorate World TB Day by showcasing research insights shared by early-career scientists and researchers in the field. The speakers spoke on four broad topics: identification of novel drug targets, development of host-directed drug therapies, transmission of tuberculosis and immunology of TB/HIV co-infections. Assistant Professor Bryan Bryson gave a highly interesting keynote address that showcased the application of engineering tools to answer fundamental biological questions, particularly in the context of tuberculosis. </ns3:p>
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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 | 0.017 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.000 | 0.002 |
| 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".