Producción científica cubana sobre biofertilizantes: un análisis bilbiométrico en revistas extranjeras
Bibliographic record
Abstract
The article shows the evolution have had the Cuban investigation about biofertilizers in foreign journals, trought the use of bibliometrics indicators, in this case they have themselves in account production indicators, scientific collaboration, as well as, the microorganisms and the crops more often investigated in the 1999-2017 period. For the analysis of the data Excel, ToolInf and Ucinet 6.0 were used. It was published 55 articles about biofertilizer in the period, the year 2011 resulted to be the most productive, and the tendency is to keep the average of the three articles per year. The foreign journal in which the cuban authors have published about biofertilizers were: Mycotaxon, Revista Colombina de Biotecnologia and Revista Mexicana de Fitopatologia. The authors who more have published were Annia Hernandez Rodriguez, Eduardo Furrazola y Ricardo A. Herrera (†), as main authors. The national institutions what more incedence in the topics are INCA, UH and IES; and the intenational institutions of bigger collaboration are: KU Leuven (Belgica), Agriculture and Agri-Food Canada and CEPROBI-IPN (Mexico). The crops more approached in the period were: maize, rice, tomato, wheat and sugar-cane; the genus most frequently studied of biofertilizer microorganisms are: Glomus, Bacillus and Pseudomonas.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.044 | 0.050 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".