Penamaan Tempat Usaha di Umakatahan : Kajian Semantik
Bibliographic record
Abstract
The purpose of this research is to analyze the naming of business places in Umakatahan. The theory used in analyzing naming is Chaer’s theory (2009). This study uses a qualitative research model. The data collection process carried out in this study used the documentation method, followed by the observing and nothing method. The data in this study are presented in a descriptive form or informal method. Based on the result of this study it was found that from 5 data on the naming of bussines places in Umakatahan, there were grammaticalmeanings. In addition, the naming process that occurs in 5 data on the naming of business premises in Umakatahan, produces 5 data based on inventors or makers, data based on new names, data based on place of origin, data based on uniqueness and new naming. So, it can be concluded that the naming of business places in Umakatahan is dominated by the process of the inventor or maker because most of the business places use the name of the owner or maker.
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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 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".