ROLLER COMPACTED CONCRETE RCC UNTUK BANGUNAN BENDUNGAN
Bibliographic record
Abstract
The using of Roller Compacted Concrete (RCC) is one of many alternatives that can be used to decrease dam construction cost. Many Roller Compacted Concrete (RCC) composition has been developed to achieve maximum compressive strength. Due to the economical consideration and the possibility of the execution, drop hammer system has been used for this research. Compression test is done after the age of the sample reaches seven, 28, 60, and 90 days. The result shows that 60/40 composition of gravel/sand has higher average compressive strength on all age of sample. The highest compressive strength the achieve is 17.78 MPa for 90 days sample. Abstract in Bahasa Indonesia : Penggunaan Roller Compacted Concrete (RCC) merupakan salah satu alternatif yang dapat digunakan untuk mengurangi biaya pembuatan konstruksi bendungan. Berbagai komposisi benda uji Roller Compacted Concrete (RCC) dibuat untuk mengetahui kuat tekan yang paling maksimal. Ditinjau dari segi ekonomis dan kemudahan pelaksanaan, maka digunakan sistem alat pemadat drop hammer. Dilakukan tes kuat tekan setelah umur benda uji masing-masing mencapai tujuh, 28, 60, dan 90 hari. Hasil penelitian menunjukkan bahwa komposisi kerikil/pasir sebesar 60/40 selalu memiliki kuat tekan rata-rata yang lebih tinggi pada semua umur benda uji. Kuat tekan terbesar pada benda uji umur 90 hari mencapai 17.78 MPa.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".