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Record W4229007258 · doi:10.51178/jsr.v3i1.495

Analisa Potensi Ekonomi Daerah Dalam Rangka Penyusunan Kebijakan Pembangunan RPJMD Kabupaten Pasaman Tahun 2021-2026

2022· article· en· W4229007258 on OpenAlexaff
Lusi Dewiana

Bibliographic record

VenueEducation Achievement Journal of Science and Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusinessGovernment (linguistics)AgricultureCorporate governanceFinanceGeography

Abstract

fetched live from OpenAlex

The results of the calculation of the LQ of the three basic sectors show a stable value from 2016 to 2020, where the Agriculture, Forestry and Fisheries Sector is stable above 2 (two), the Water Supply Sector, Waste Management, Waste and Recycling and the Government Administration Sector, Defense and Mandatory Social Security are stable above number 1 (one) The three basic sectors obtained are relevant to the mission of the Regional Head, namely the Agriculture, Forestry and Fisheries Sector which is relevant to mission 5 "Realizing a People's Economy Based on Local Excellence", the Water Supply, Waste Management, Waste and Recycling Sector is relevant to mission 4 "Improving Infrastructure Capacity ” and the Mandatory Government Administration, Defense and Social Security Sector relevant to mission 6 “Realizing Good and Clean Governance”. This shows that the development of the basic sector will be interrelated with the achievement of the RPJMD mission. So with a focus on developing the three basic sectors, it will support the achievement of missions 4, 5 and 6 of Pasaman Regency.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.031
GPT teacher head0.330
Teacher spread0.299 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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Same venueEducation Achievement Journal of Science and ResearchSame topicWaste Management and RecyclingFrench-language works237,207