BIMA PORT AND THE BIMA SULTANATE IN ARCHAEOLOGICAL STUDIES
Bibliographic record
Abstract
The archipelago's ancient spice trade involved many regions and one of them was Bima during the period from Kerajaan Bima to Kesultanan Bima. Bima has a port which is hidden from the southern route via Laut Flores, so to reach it the traders have to go along Bima Bay. This research raises issues related to the background of the placement Bima port and Bima Sultanate complex and also Bima port’s characteristics. This archaeological research uses archaeological, landscape and historical data that collected through surveys, observations and literature studies to be analyzed using data analysis, landscape analysis and comparative analysis. The results of this research are that the placement of the Bima port and the Bima Sultanate complex is based on the history of Bima and the location is safe. The location of the Bima port is suitable as a place to unload anchor, shelter from pirates and the wind, and also to refill supplies for traders. Bima Port is classified as a small port because its commodities are not the main commodities for archipelago trade and the number and variety of arrivals is small. The conclusion is Bima port played a major role in the development of the Bima Kingdom and Sultanate as a place of trade and access that connected Bima with other regions or kingdoms. The port plays as dealer for commercial commodities from the region and its surroundings to be brought to larger cities or ports.
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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 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".