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Record W7029268261

Keragaan Karakter Morfo-Agronomis Beberapa Genotipe Kacang Buncis (Phaseolus vulgaris L.) di Kota Bukittinggi, Sumatra Barat

2024· other· id· W7029268261 on OpenAlexaff

Bibliographic record

VenueAndalas University eThesis (Andalas University) · 2024
Typeother
Languageid
Field
Topic
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsNucleofectionTerm (time)Population
DOInot available

Abstract

fetched live from OpenAlex

Buncis (Phaseolus vulgaris L.) merupakan sayuran yang mempunyai peluang pasar yang cukup luas dan sumber protein nabati yang murah dan mudah dikembangkan. Produktivitas kacang buncis masih rendah, sehingga perlu melakukan kegiatan pemuliaan tanaman untuk memperoleh genotipe-genotipe kacang buncis yang memiliki daya hasil tinggi. Penelitian ini bertujuan untuk mengetahui keragaman, menduga nilai heritabilitas arti luas karakter morfo-agronomis, dan memahami hubungan antar karakter pada genotipe kacang buncis yang diuji. Penelitian telah dilaksanakan bulan Januari hingga April 2024 di Kota Bukittinggi, Sumatra Barat. Rancangan percobaan yang digunakan adalah Rancangan Acak Lengkap (RAL) dengan perlakuan 6 genotipe kacang buncis. Karakter yang diamati terdiri atas karakter kualitatif dan kuantitatif. Karakter kualitatif disajikan dalam bentuk data deskriptif sedangkan karakter kuantitatif dianalisis secara statistik dengan uji F pada taraf 5% dan karakter yang berbeda nyata, dilanjutkan dengan uji Duncan’s New Multiple Range Test (DNMRT) pada taraf 5%. Hasil menunjukkan terdapat keragaman antar genotipe pada karakter kualitatif yaitu sudut ujung daun, derajat kelengkungan polong, bentuk biji, warna primer biji dan sebaran warna sekunder biji. Umumnya karakter kuantitatif memiliki ragam genetik yang luas kecuali pada karakter diameter batang, lebar daun dan jumlah biji per polong. Karakter yang diamati memiliki nilai heritabilitas arti luas yang tinggi kecuali pada karakter diameter batang dan lebar daun. Karakter panjang polong dan jumlah biji per tanaman memiliki korelasi positif yang kuat dan nyata terhadap karakter bobot polong per tanaman.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.178
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0110.007
Science and technology studies0.0030.003
Scholarly communication0.0010.002
Open science0.0060.003
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0240.034

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 head0.011
GPT teacher head0.195
Teacher spread0.183 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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