MétaCan
Menu
Back to cohort
Record W2956340917 · doi:10.5539/jas.v11n12p11

External Quality Control: Official Results of Forage Seeds Quality

2019· article· en· W2956340917 on OpenAlexvenueno aff
Ricardo Miotto Ternus, Jerffeson Araújo Cavalcante, Géri Eduardo Meneghello, Vinícius Jardel Szareski, Ivan Ricardo Carvalho, Andréa Bicca Noguez Martins, Giordano Gelain Conte, Francisco Amaral Villela

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsGerminationForageCertificationConformityQuality (philosophy)AgronomyMathematicsGeographyBiologyHorticultureLawPolitical science

Abstract

fetched live from OpenAlex

The objective of this work to evaluate the official results of seeds quality of ryegrass, black oat grass, sudangrass and pearl millet, originated from commercial establishments from the State of Santa Catarina. Lots of forage seeds sampled in the state of Santa Catarina in the year of 2013 to 2015, presented low physiologic and physic quality, being the main criteria of disapproval the physic purity and germination. The samples of forage seeds from C1 and C2 categories collected in Santa Catarina present superior quality in relation to the non-certified S1 and S2. The quality of ryegrass seeds (national) showed below the legal standards established, independent of the year, for the physic purity and germination criteria. Although, for the ryegrass lots (imported) there was none disapproval related to germination and physic purity being out of the tolerated limits.The germination and physic purity indexes, for sudangrass lots presented conformity index adequate to the tolerated limits allowed by legal standards. In the other hand, for the same species, the criteria for number of other cultivated species presented 100% of disapproval for the analyzed lots in the non-certified categories in 2013. Lots of pearl millet seeds, with exception of those from the C2 category sampled in 2014, presented in conformity to the legal standards required, being, in comparison with the other species, the one that showed lower non-conformity degree in the analyzed period.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.278
Teacher spread0.247 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicAgricultural and Food SciencesFrench-language works237,207