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Profil Plasma Nutfah dan Jenis Penyakit Pisang Lokal asal Pandeglang Banten

2020· article· en· W4205368836 on OpenAlexaff
Nani Maryani, Dewi Susilawati, Indah Juwita Sari, Rida Oktorida Khastini

Bibliographic record

VenueFaktor Exacta · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanana Cultivation and Research
Canadian institutionsCrown Investments Corporation (Canada)
Fundersnot available
KeywordsGermplasmBiologyBiodiversityHorticultureGeographyEcology

Abstract

fetched live from OpenAlex

Banana is the most favorite fruits in the world. Indonesia is in the center of origin and diversity of banana in Southeast Asia. Banten is one of the most banana producer in Indonesia. However, no information on banana diversity and its associated disease available from this province. In this paper, we explored Kabupaten Pandeglang in its diversity of banana and its associated disease. Eleven local banana germplasm were identified with their associated disease. Fusarium wilt, Sigatoka, and Blood disease are the most common diseases found on those varieties. Seven local banana germplasm are described in this paper. These information are very important to preserved biodiversity of Indonesia and will be useful for future food security and sustainability.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.063
GPT teacher head0.241
Teacher spread0.178 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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