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Record W4399094874 · doi:10.47637/agrimals.v2i2.619

ANALISIS TINGKAT PENDAPATAN DAN KESEJAHTERAAN PETANI UBI KAYU DI KECAMATAN BUMI NABUNG KABUPATEN LAMPUNG TENGAH

2022· article· en· W4399094874 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Agriculture and Animal Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Development and Management
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsWelfareAgricultural scienceAgricultureSocioeconomicsAgricultural economicsGeographyBusinessEconomicsBiology

Abstract

fetched live from OpenAlex

The purpose of this study is to analyze the income level and welfare of cassava farmers in Bumi Nabung Ilir Village, Bumi Nabung District, Central Lampung Regency. Considering the fact that Bumi Nabung Ilir Village has the largest land area and cassava production in Bumi Nabung district, this location was carefully selected, but there are still many farmers classified as low income, About 997 households. Income analysis and welfare analysis are used as data analysis methods. The sample used in this study included 41 individuals of her who used a targeted sampling technique which is based on farmers owning land and farming experience. As a results, according to the BPS category, the income level of cassava farmers in Bumi Nabung Ilir Village was classified as medium income with a percentage of 46.34%. The income of cassava farming on the variable cost is Rp. 7,977,561/ha/MT and the income on the total cost is Rp. 7,639,467/ha/MT. The results of the study from 41 respondents can be concluded that the level of welfare is at a moderate level of welfare, namely with a score of 84

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.010
GPT teacher head0.195
Teacher spread0.186 · 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