Parasitology of the twenty-first century: are we moving in the right direction?
Bibliographic record
Abstract
For thousands of years, parasitic infections have represented a constant challenge to human health. Despite constant progress in science and medicine, the challenge has remained mostly unchanged over the years, partly due to the vast complexity of the host-parasite-environment relationships. Over the last century, our approaches to these challenges have evolved through considerable advances in science and technology, offering new and better solutions. Unfortunately, in the twenty-first century, this diagnostic evolution was suddenly confronted with a dramatic change of biological relationships, never witnessed in history before the uncontrolled expansion of the human population, globalization and hyperconnectivity technology have exerted a massive socioeconomic impact on individuals, communities and the environment, sending a ripple effect throughout the world of parasites. Urbanization, pollution and the unsustainable exploitation of natural resources have caused shifts in biomass and the fragmentation of habitats, leading to the movement of parasites into new hosts and territories. At the same time, changes in human population structure and distributions due to armed conflict and poverty created massive migration of entire nations and communities, resulting in the redistribution of parasitic diseases. To make the situation worse, the population of many receiving countries of North America and Europe is ageing, leading to a critical shortage of a specialized workforce essential to deal with the new diagnostic challenges. Unfortunately, this vicious circle is not yet apparent to all. The highly specialized field of parasitology is at a particular risk for such major crises in the near future. Heightened awareness of such risks is an essential step to start discussions and planning to mitigate these very real health threats.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.014 | 0.024 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.012 | 0.025 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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".