Bibliographic record
Abstract
Kegiatan ekstrakurikuler perlunya di terapkan pada dunia pendidikan agar tidak adanya kegiatan proses belajar mengajar yang monoton interaksi antara dosen dan mahasiswa, dalam kesempatan ini mahasiswa program pascasarjana teknik sipil Universitas Muslim Indonesia dibawah kepemimpinan Ketua Program Studi Teknik SIpil Dr. Ir. Hj. St. Maryam Hafram, M.T melaksanakan kegiatan yang disebut BENCHMARKING PROGRAM PASCASARJANA TEKNIK SIPIL – UNIVERSITAS MUSLIM INDONESIA TAHUN 2017, Selama 5 (lima) hari terhitung sejak tanggal 08 November 2017 – 12 November 2017 dengan melaksanakan kunjungan ke beberapa Negara yaitu Malaysia – Singapore & Batam (Indonesia).Adapun tujuan pelaksanaan kegiatan tersebut adalah :1.Mengunjungi project prestigious yang berada pada daerah tersebut dan melakukan interaksi langsung dengan owner dan project manager tentang pelaksanaannya. 2.Mengembangkan pendidikan bagi mahasiswa dengan memberikan pengalaman akan penggunaan teknologi pada proyek-proyek yang akan dikunjungi.3.Bertemu dengan pihak pemerintah terkait dan berinteraksi langsung tentang pertumbuhan pembangunan yang berkaitan dengan keteknik sipilan.4.Mengunjungi lokasi – lokasi pasca konstruksi yang menggunakan perencanaan & teknologi tinggi yang tidak terdapat di Indonesia terkhusus Sulawesi Selatan.5.Memberikan pengalaman bagi mahasiswa untuk dapat berinteraksi langsung.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.015 |
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".