Solusi inovasi dan kemitraan peremajaan konstruksi kapal kayu nelayan 1 GT dan 3 GT berbasis teknologi material jenis kayu cepat tumbuh untuk mendorong industri galangan kapal masyarakat di wilayah pesisir Provinsi Riau
Bibliographic record
Abstract
Tujuan utama pengabdian masyarakat adalah penerapan inovasi Teknologi Material Kayu Komposit dengan memanfaatkan material spesies kayu dengan masa panen pendek (fast growing species) di Desa Teluk Nilap, Kecamatan Kubu Babussalam, Kabupaten Rokan Hilir Provinsi Riau diharapkan mampu memberi solusi permasalahan akan kelangkaan bahan material kayu dengan spesifikasi tertentu guna peremajaan kapal nelayan masyarakat 1 GT dan 3 GT guna mendukung keberlanjutan industri galangan kapal di Wilayah Pesisir Provinsi Riau. Metode pendekatan yang diterapkanuntuk pengabdian masyarakat adalah menggabungkan antara teknologi kayu komposit dengan budaya kearifan lokal yang berorientasikan material kapal berbasis kayu. Untuk kemitraan pembuatan model fisik skala penuh (full scale) kapal kayu nelayan ukuran 1 GT dan 3 GT di industri galangan kapal masyarakat milik H. Muhammad Ali Napiah di Desa Teluk Nilap.Hasil utama dari pengabdian kepada masyarakatmembuktikan bahwa penerapan teknologi material kayu komposit menggunakan jenis kayu cepat tumbuh untuk konstruksi kapal nelayan masyarakat ukuran 1 GT dan 3 GT telah diterapkan pada industri galangan kapal kayu.Sinergitas inovasi dan kemitraan diyakini mendorong peningkatan perekonomian masyarakat nelayan di Wilayah Pesisir Provinsi Riau dengan didukung industri galangan kapal mandiri.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".