Bibliographic record
Abstract
Darwiniana agradece a los arbitros por su tiempo y esfuerzo para mejorar la calidad del contenido de nuestra revista. Expresamos nuestro reconocimiento a los siguientes investigadores por el arbitraje de los articulos presentados para el Vol. 2(1). 2014: Pedro Acevedo-Rodriguez, National Museum of Natural History, Smithsonian Institution, Washington D. C., United States of America. Maria Gabriela Aguirre, Facultad de Ciencias Naturales e Instituto Miguel Lillo, Universidad Nacional de Tucuman, San Miguel de Tucuman, Argentina. Felipe Amorim, Departamento de Biologia Vegetal, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, Sao Paulo, Brasil. Gabriel Araujo Santos, Colegio Pedro II, CSCII, Sao Cristovao, Rio de Janeiro, Brasil. Ignacio Barberis, Facultad de Ciencias Agrarias, Universidad Nacional de Rosario, Zavalla, Argentina. Manuel Joaquin Belgrano, Instituto de Botanica Darwinion, CONICET-ANCEFN, San Isidro, Argentina. Marcelo Cabido, Instituto Multidisciplinario de Biologia Vegetal, Universidad Nacional de Cordoba, CONICET, Cordoba, Argentina. Aylen Capparelli, Universidad Nacional de La Plata, CONICET, La Plata, Argentina. Alexis Cerezo Blandon, Departamento de Metodos Cuantitativos y Sistemas de Informacion, Facultad de Agronomia, Universidad de Buenos Aires, Ciudad Autonoma de Buenos Aires, Argentina. Laura del Puerto Garcia, Centro Universitario Regional Este, Universidad de la Republica, Maldonado, Uruguay. Mariano Devoto, Facultad de Agronomia, Universidad de Buenos Aires, Ciudad Autonoma de Buenos Aires, Argentina. Alejandra Korstanje, Instituto Superior de Estudios Sociales, Universidad Nacional de Tucuman, CONICET, San Miguel de Tucuman, Argentina. Ramiro Pablo Lopez, Herbario Nacional de Bolivia, Instituto de Ecologia, Universidad Mayor de San Andres, La Paz, Bolivia. Guillermo J. Martinez-Pastur, Centro Austral de Investigaciones Cientificas, CONICET, Ushuaia, Argentina. Nurit Olizewski, Instituto Superior de Estudios Sociales, Universidad Nacional de Tucuman, CONICET, San Miguel de Tucuman, Argentina. Luis Ignacio Perez, Catedra de Ecologia, Instituto de Investigaciones Fisiologicas y Ecologicas Vinculadas a la Agricultura, Facultad de Agronomia, Universidad de Buenos Aires, CONICET, Ciudad Autonoma de Buenos Aires, Argentina. Liliane E. Petrini, Societa Micologica di Lugano, Lugano, Svizzera. Orlando Petrini, Cantonal Institute of Microbiology, Bellinzona, Svizzera. Marcelo Pinto Marcelli, Instituto de Botânica (IBt), Sao Paulo, Brasil. Maria Lelia Pochettino, Universidad Nacional de La Plata, CONICET, La Plata, Argentina. Ghillean T. Prance, Royal Botanic Gardens, Kew, United Kingdom. Juan Manuel Rodriguez, Centro de Ecologia y Recursos Naturales Renovables Dr. R. Luti, Facultad de Ciencias Exactas, Fisicas y Naturales, Universidad Nacional de Cordoba, Cordoba, Argentina. Andrea I. Romero, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, CONICET, Ciudad Autonoma de Buenos Aires, Argentina. Gabriel Hugo Rua, Catedra de Botanica Agricola, Facultad de Agronomia, Universidad de Buenos Aires, Ciudad Autonoma de Buenos Aires, Argentina. Sebastian A. Stenglein, Facultad de Agronomia, Universidad Nacional del Centro de la Provincia de Buenos Aires, Azul, Argentina. Michael Sundue, Pringle Herbarium, Plant Biology Department, University of Vermont, Burlington, United States of America. Markus N. Thormann, Aquilon Environmental Consulting Ltd., Edmonton, Canada.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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; both teacher heads agree on what is shown here.
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".