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Record W2911701813 · doi:10.5539/jas.v11n3p421

Qualitative and Quantitative Evaluation Protocol of Baccharis Seed Germination

2019· article· en· W2911701813 on OpenAlexvenueno aff
María Alejandra Moreno-Pizani, A. Ramírez, Hugo Thaner dos Santos, Ana Dionísia da Luz Coelho Novembre, Lorena Isabel Guevara-Orozco, Franklin Paredes‐Trejo, Fábio Ricardo Marin, Nildo da Silva Dias, Patrícia Angélica Alves Marques

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsGerminationBaccharisBiologyHorticultureBotanyAsteraceae

Abstract

fetched live from OpenAlex

Baccharis trimera (Less.) DC (E1) and Baccharis crispa Spreng. (E2) possess potential antimicrobial and anti-inflammatory properties. Qualitative and quantitative information on seed germination on these species is scarce. The objective of this investigation was to establish a protocol for evaluating seed germination of E1 and E2 and to analice the scoring and curve fitting by the Germinator package, for different periods of germination were between 0.93 and 0.99. Both species showed differences in germinability and mean germination time, 27 days for E1 and 20 days for E2. The germination dispersion showed that E1 germination was homogeneous, with differences in growth pattern, whereas the results on germination of E2. The mean speed of germination determined with the experimental data was close to the values obtained by the Germinator package, with a maximum germination of more than 34%, proving that the software was efficient for evaluating germination.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.059
GPT teacher head0.383
Teacher spread0.324 · 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 designBench or experimental
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

Citations2
Published2019
Admission routes1
Has abstractyes

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