Bibliographic record
Abstract
Desa Mekarmulya adalah salah satu desa dari 10 desa yang masuk dalam wilayah administratif Kecamatan Telukjambe Barat, Kabupaten Karawang. Dikepalai oleh seorang kepada desa dan dibantu oleh seorang sekretaris desa dan segenap perangkat desa. Desa Mekarmulya dikenal sebagai sentral industri rumahan (home industry) pembuatan batu bata merah pres. Hampir semua warga menjadi pembuat batu bata merah. Namun lambat laun usaha ini kian lesu dan kalah bersaing dengan adanya batu bata ringan. Lesunya penjualan batu bata merah ini juga dirasakan langsung oleh para buruh yang bekerja di salah satu pengrajin batu bata merah. Di sisi lian, terdapat potensi bekas galian material batu bata merah menjadi kolam untuk budi daya ikan air tawar sebagai tambahan penghasilan bagi para pengrajin bata merah yang mulai menurun. Untuk sementara waktu, sebagai permulaan ikan yang direkomendasikan adalah ikan nila karena mudah beradaptasi dengan lingkungan dan cepat berkembang biak. Selain budi daya ikan dan dijual secara mentah, juga disarankan untuk menjual hasil ikan tersebut berupa makanan olahannya seperti nugget, ikan asap, dan lain-lain. Kata kunci: Mekarmulya, Batu Bata Merah, Budidaya, Ikan Air Tawar Mekarmulya Village is one of the 10 villages included in the administrative area of Telukjambe Barat District, Karawang Regency. Headed by a village officer and assisted by a village secretary and all village officials. Mekarmulya Village is known as the center of the cottage industry for making pressed red bricks. Almost all residents become red brick makers. However, gradually this business became sluggish and could not compete with the light bricks. The sluggish sales of red bricks were also felt directly by the workers who worked in one of the red brick craftsmen. On the other side, there is the potential for the ex-excavated red brick material to become a pond for freshwater fish resources as an additional stage for the red brick craftsmen, which is starting to decline. For a while, the fish that refused to start was tilapia because it was easy to adapt to the environment and quickly reproduced. Apart from cultivating fish and selling it raw, it is also advisable to sell fish products in the form of processed food such as nuggets, smoked fish, and others. Keywords: Mekarmulya, Red Bricks, Cultivation, freshwater fish
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.049 | 0.014 |
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".