MétaCan
Menu
Back to cohort
Record W2756113297 · doi:10.5539/jas.v9n10p145

Growth and Evaluation of Phenolic Compounds in Physalis angulata L. at Two Different Periods in the Bahia Reconcavo, Brazil

2017· article· en· W2756113297 on OpenAlexvenueno aff
Claudia B. de Abreu, Fabrício Mendes Miranda, Torben Grael Dos Santos Rodrigues, Fábio de S. Dias

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Medicinal Plants
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsHorticultureDry weightBotanyBiologyStem-and-leaf displayTraditional medicineMedicine

Abstract

fetched live from OpenAlex

Physalis angulata L. has aroused the interest of the researchers, since its properties come from the great therapeutic potential attributed to the commonly called substances of physalins. However, its cultivation in the study region lacks important information on the species adaptation to local soil and climate characteristics. The aim of this study was to evaluate the growth and concentration of phenolic compounds in P. angulata L. at two different periods in the Bahia Reconcavo. The experimental design was completely randomized blocks with 10 replicates. We evaluated the stem height and diameter, number of leaves and fruits, dry mass of leaves, stems and roots, leaf area, specific leaf area, leaf area ratio, leaf mass ratio and total phenolics, total flavonoids and antioxidant activity in the different organs of the plant. The growth was favorable from April to June. However, the concentration of phenolic compounds was higher in the period from December to February. The cultivation period influenced the growth and concentration of phenolic compounds in P. angulata L. in the Bahia Reconcavo.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.349
Teacher spread0.309 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicPhytochemicals and Medicinal PlantsFrench-language works237,207