Exploring the Evolution of Trypanosoma cruzi and the Emergence of Chagas Disease in the Context of Environmental Change
Bibliographic record
Abstract
The Stockholm Paradigm is an evolutionary synthesis that explains the emergence of novel pathogens in the context of environmental disturbances. Considering the urgent climate change situation, anticipation stands as key to prevent and mitigate the effects that climate change can have in the emergence of pathogens. However, the success of preventive measures is hindered by a limited knowledge of the interplaying dynamics between biology, environment, and culture leading to emerging infectious diseases. For many decades, bioarcheologists have been gathering data on past human–environment interactions, therefore contributing to the conversation. Archaeoparasitology, at the intersection between pathology, bioarchaeology, and biology, is uniquely placed to enquire about the circumstances that favored the emergence of novel pathogens in the past. We illustrate this task by reviewing the existing knowledge on the evolution of Trypanosoma cruzi and emergence of Chagas disease. When the scholarship on Chagas is completed with the lessons learned from the Stockholm Paradigm, this provides a long-term perspective on environmental change and human relations leading to the emergence of an infectious disease.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".