Roadmap for tuberculosis elimination in Latin American and Caribbean countries: a strategic alliance
Bibliographic record
Abstract
On July 4–5, 2016, representatives of the Asociación Latinoamericana de Tórax (ALAT), the European Respiratory Society (ERS) and of the Panamerican Health Organization (PAHO) met in Santiago de Chile to attend the VIII Regional Meeting of American Low Tuberculosis Incidence Countries. This meeting took place in connection with the 2016 ALAT Congress. Among the meeting attendees there were managers of national tuberculosis (TB) programmes and pulmonologists belonging to the ALAT Tuberculosis Dept. Joint ALAT/ERS/PAHO strategic alliance develops roadmap for TB elimination in Latin American and Caribbean countries The Authors with to thank Lia D'Ambrosio and Rosella Centis (WHO Collaborating Centre for TB and Lung Disease, Tradate, Italy) for their technical support in finalising the manuscript. In addition, the authors thank the participants of first meeting of the GILA-TB as part of the ERS/ALAT LATSINTB Project (Adriana Maria Montoya Salazar, Colombia; Alfredo Cruz Lagunas, Mexico; Ana Putruelle, Argentina; Carlos Awad García, Colombia; Carlos Peña Mantinetti, Chile; Cartos Torres, Colombia; Domingo Palmero, Argentina; Edilberto Gonzalez Ochoa, Cuba; Edwin Herrera Flores, Peru; Gabriela Manonelles, Argentina; Giovanni Battista Migliori, Italy; Joaquin Zúñiga, Mexico; Kareen Suarez, Chile; Adrian Rendon, Mexico; Marcela Muñoz, Mexico; Margareth Dalcolmo, Brazil; Mario Chavez, Chile; Miguel Angel Salazar, Mexico; Mónica Sanchez, Chile; Nelly Cavieres, Chile; Raquel Duarte, Portugal; Roberto Accinelli Tanaka, Lima; Sandra Ariza Matiz, Colombia; Selene Manga, Peru; Tania Herrera, Chile; Tulio Torres, Guatemala; and Zhenia Fuentes, Venezuela) and the VIII Reunión Regional de Países de Baja Incidencia de Tuberculosis, Las Americas (Adrian Rendon, México; Adriana Maria Montoya Salazar, Colombia; Alvaro Díaz, Chile; Alvaro Yañez del Villar, Chile; Carlos Awad García, Colombia; Carlos A. Torres Duque, Colombia; Cecilia Coitinho Azevedo, Uruguay; Chris Archibald, Canada; Edilberto González Ochoa, Cuba; Ernesto Moreno Naranjo, Colombia; Fabiola Arias, Chile; Getahun Gebre Haileyesus, Switzerland; Giovanni Battista Migliori, Italy; Gonzalo Solis, Chile; Jorge Victoria, Panama; Jorge Rodríguez De Marco, Uruguay; José Raúl de Armas Fernández, Cuba; Karla Kohan, Chile; Marcela Moreno Lunes, Chile; Marcelo Vila, Argentina; Marcos Gallardo, Chile; Mariela Contrera, Uruguay; Martha Angelica García Avilés, México; Miguel Salazar, Mexico; Mirtha Del Granado, USA; Paula Lasserra Echenique, Uruguay; Raquel Duarte Portugal; Raúl Diaz Rodríguez, Cuba; Roberto Del Aguila, Chile; Rosario Lepe Lepe, Chile; Sandra Ariza Matiz, Colombia; Tania Herrera, Chile; Zeidy Mata Azofeifa, Costa Rica; Zhenia Fuentes, Venezuela; and Zulema Torres Gaete, Chile).
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".