Kajian Jenis-jenis Kayu dan Perhitungan Volume Bahan Pembuatan Kapal Nelayan Tradisional di Kecamatan Bangkurung Kabupaten Banggai Laut
Bibliographic record
Abstract
This study aims to determine the types of wood used in making traditional boats and to determine the calculation of the volume of materials needed for making traditional fishing boats in Kalupapi Village and Bone-Bone Village, Bangkurung District, Banggai Laut Regency. The research method used a survey method applied in two ways, namely interviews using questionnaires and direct sample measurements. The results of this study indicate that traditional fishing boats in Kalupapi Village and Bone-Bone Village are made of wood, which not only provides strength and durability, but also supports environmental sustainability by utilizing natural resources available around the village. The types of wood used are meranti wood and ironwood. To calculate the estimated wood requirements in boat construction, which include the volume of boards and the length and diameter of the mahera, the board volume coefficient (Cp), the mahera length coefficient (Clm), and the mahera diameter coefficient (Cd) can be used. In this study, the results obtained are Cp 0.1604, Clm 9.300, and Cd 0.498.
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 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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".