Penentuan Sektor Unggulan Dalam Perekonomian Wilayah Kabupaten Langkat Pendekatan Sektor Pembentuk Pdrb
Bibliographic record
Abstract
The determination of leading sector of economy of the regency with the PDRB forming sector approach.Economic growth and the process is the main conditionfor maintaining regional economic development.To spur the reginon's economic growth rate and increase its contribution to the formation of gross regional domestic total (GDP), then the development of leading sectors can be made as a driver of regional economic development.With the development of the region's leading sector is expected to increase the economic growth of the region itself.Focus of this research is to determine the superior economic sector in Langkat regency as a consideration in economic development planning.The analysis used is Location quotient (LQ), Tipology klassen and shife share.LQ analysis is used to identify the base sector, tipology klassen analysis is used to determine sector growth classification and shife share is used to determine the leading sector and see how big contribution of superior sector of langkat regency in economic development.The leading sector of Langkat Regency are Agriculture Sector and Electricity Sector.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".