First Colombian consensus on congenital Chagas and clinical approach for women of child-bearing age diagnosed with Chagas
Bibliographic record
Abstract
Congenital transmission of Chagas disease has not been extensively studied in Colombia, and there are no standardized processes in the health system regarding the specific diagnosis, treatment and follow-up of this disease. To generate recommendations on congenital Chagas disease and Chagas in women of childbearing age in Colombia, a consensus of experts was developed. An extensive literature search through the Medline database was carried out using the MeSH terms: «Chagas disease/congenital», «prevention and control», «diagnosis», «therapeutics» and «pregnancy». Appropriate abstracts were selected and the full texts were analyzed. The relevant information was synthesized, classified, and organized into tables and figures and was presented to a panel of experts, which was composed of 30 professionals from various fields. Based on the Delphi methodology, three rounds of consultation were conducted. The first and second rounds were based on electronic questionnaires that measured the level of consensus of each question among the participants. The third round was based on a face-to-face discussion focusing on those questions without consensus in the previous consultations. Theevidence was adapted to national circumstances on a case-by-case basis, and the content the final document was approved. These recommendations are proposed for use in routine medical practice by health professionals in Colombia.
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 | 0.028 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".