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Record W2888648707

Producción científica cubana sobre biofertilizantes: un análisis bilbiométrico en revistas extranjeras

2018· article· es· W2888648707 on OpenAlexaboutno aff
Maida Daylin Peña Borrego, María Rosa de Zayas Pérez, Rosa Margarita Rodríguez Fernández

Bibliographic record

VenueXV Congreso Internacional de Información Info'2018 · 2018
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicPlant and soil sciences
Canadian institutionsnot available
Fundersnot available
KeywordsBiofertilizerSugar caneBibliometricsHorticulturePolitical scienceAgricultural scienceGeographyBiologyLibrary science
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.005

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.

Opus teacher head0.019
GPT teacher head0.256
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueXV Congreso Internacional de Información Info'2018Same topicPlant and soil sciencesFrench-language works237,207