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Record W2911086533 · doi:10.29244/agrob.7.1.62-68

Perbaikan Teknik Pembrongsongan melalui Aplikasi Pestisida untuk Meningkatkan Kemulusan Buah Jambu Kristal (Psidium guajava L)

2019· article· id· W2911086533 on OpenAlexaff
Yosephine Sista Parameswara, Slamet Susanto

Bibliographic record

VenueBuletin Agrohorti · 2019
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHorticultureBiology

Abstract

fetched live from OpenAlex

<p style="text-align: justify;">Jambu ‘kristal’ merupakan kultivar unggulan jambu biji dan memiliki pasar yang baik di Indonesia. Jambu kristal memiliki rasa yang manis, tekstur renyah, vitamin C, dan kandungan lain yang bermanfaat. Kualitas merupakan masalah utama dalam budidaya jambu ‘kristal’, salah satunya adalah tingkat kemulusan buah. Penelitian ini bertujuan mengetahui pengaruh bahan aktif pestisida yang digunakan pada teknik pembrongsongan buah terhadap tingkat kemulusan buah. Penelitian dilaksanakan di Kebun Percobaan Cikabayan dan Laboratorium Pascapanen, Departemen Agronomi dan Hortikultura, Institut Pertanian Bogor pada Bulan Februari 2017 hingga Agustus 2017. Bahan yang digunakan pada teknik pembrongsongan adalah bahan aktif pestisida: Klorpirifos, Abamektin, dan Mankozeb. Hasil penelitian menunjukkan bahwa perlakuan bahan aktif pestisida memberikan pengaruh yang sangat nyata pada peubah kemulusan buah. Perlakuan bahan aktif pestisida meningkatkan kemulusan buah hingga dua kali lipat. Perlakuan bahan aktif pestisida tidak memberikan pengaruh nyata pada peubah diameter, kelunakan, bobot, PTT, dan ATT.</p>

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient 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 score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.007

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 head0.007
GPT teacher head0.192
Teacher spread0.185 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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