Update on <i>Giardia</i>: Highlights from the seventh International <i>Giardia</i> and <i>Cryptosporidium</i> Conference
Bibliographic record
Abstract
Although Giardia duodenalis is recognized as one of the leading causes of parasitic human diarrhea in the world, knowledge of the mechanisms of infection is limited, as the pathophysiological consequences of infection remain incompletely elucidated. Similarly, the reason for and consequences of the very specific genome-organization in this parasite with 2 active nuclei is only partially known. Consistent with its tradition, the 7th International Giardia and Cryptosporidium Conference (IGCC 2019) was held from June 23 to 26, 2019, at the Faculty of Medicine and Pharmacy of the University of Rouen-Normandie, France, to discuss current research perspectives in the field. This renowned event brought together an international delegation of researchers to present and debate recent advances and identify the main research themes and knowledge gaps. The program for this interdisciplinary conference included all aspects of host-parasite relationships, from basic research to applications in human and veterinary medicine, as well as the environmental issues raised by water-borne parasites and their epidemiological consequences. With regard to Giardia and giardiasis, the main areas of research for which new findings and the most impressive communications were presented and discussed included: parasite ecology and epidemiology of giardiasis, Giardia-host interactions, and cell biology of Giardia, genomes and genomic evolution. The high-quality presentations discussed at the Conference noted breakthroughs and identified new opportunities that will inspire researchers and funding agencies to stimulate future research in a "one health" approach to improve basic knowledge and clinical and public health management of zoonotic giardiasis.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.020 | 0.011 |
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".