What did we learn from the genome-wide association study for tuberculosis susceptibility?: Figure 1
Bibliographic record
Abstract
The genetics literature is replete with results of candidate-gene association studies published mostly before the genome-wide association study (GWAS) became the new standard, but also continuing to this date. Their track record for replication is generally poor and discrepancies are typically attributed to differences in populations or environments. Are these results of any value, or should they be summarily discarded? Recent results from a GWAS for tuberculosis (TB) provide data that might put this question in perspective.1 TB is a serious health issue in the developing world, due to infection by Mycobacterium tuberculosis (MTB). Currently, about one third of the world's population is infected by MTB and 1/10 will develop active TB (http://www.who.int/tb/en/). Improved understanding of mechanisms of pathogenesis and host resistance is essential for improved control of TB. Human genetics is an indispensable tool for enhancing the understanding of the molecular basis of many common diseases. There is evidence that genetic factors may be involved in susceptibility to TB infection and activation of TB. This can be demonstrated by the fact of obvious ethnic differences. Blacks have about 1.5–2-fold greater risk than whites as shown by the tuberculin skin test,2 and concordance for TB is 2.5-fold higher among monozygotic than dizygotic …
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 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".