EWET: Data collection and interface for the genetic analysis of Echinococcus multilocularis based on EmsB microsatellite
Bibliographic record
Abstract
Evolution and dispersion history on Earth of organisms can best be studied through biological markers in molecular epidemiological studies. The biological diversity of the cestode Echinococcus multilocularis was investigated in different cladistic approaches. First the morphological aspects were explored in connection with its ecology. More recently, molecular aspects were investigated to better understand the nature of the variations observed among isolates. The study of the tandemly repeated multilocus microsatellite EmsB allowed us to attain a high genetic diversity level where other classic markers have failed. Since 2006, EmsB data have been collected on specimens from various endemic foci of the parasite in Europe (in historic and newly endemic areas), Asia (China, Japan and Kyrgyzstan), and North America (Canada and Alaska). Biological data on the isolates and metadata were also recorded (e.g. host, geographical location, EmsB analysis, citation in the literature). In order to make available the data set of 1,166 isolates from classic and aberrant domestic and wild animal hosts (larval lesions and adult worms) and from human origin, an open web access interface, developed in PHP, and connected to a PostgreSQL database, was developed in the EmsB Website for the Echinococcus Typing (EWET) project. It allows researchers to access data collection, perform genetic analyses online (e.g. defining the genetic distance between their own samples and the samples in the database), consult distribution maps of EmsB profiles, and record and share their new EmsB genotyping data. In order to standardize the EmsB analyses performed in the different laboratories throughout the world, a calibrator was developed. The final aim of this project was to gather and arrange available data to permit to better understand the dispersion and transmission patterns of the parasite among definitive and intermediate hosts, in order to organize control strategies on the ground.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.098 | 0.058 |
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".