Bibliographic record
Abstract
Pegipegi.com (Go Online Destination) merupakan salah satu biro atau agen perjalanan (Online Travel Agent) berbasis online yang tujuan memberikan kemudahan dalam mengatur dan merancang perjalanan baik dari segi transportasi maupun akomodasi. Dengan pegipegi.com, calon konsumen dapat melakukan reservasi hotel ataupun tiket pesawat dengan biaya yang murah dan kemudahan dari segi transaksi.Pegipegi.com didirikan pada tanggal 1 Januari 2012. Meskipun travel agen ini masih tergolong baru, akan tetapi pegipegi sudah memiliki begitu banyak afiliasi dengan hotel dan maskapai penerbangan di seluruh wilayah Indonesia. Hingga kini, pegipegi tercatat sudah memiliki afiliasi dengan lebih dari 1700 hotel dan penginapan di semua daerah di Indonesia dan beberapa maskapai penerbangan seperti Citilink, Sriwijaya Air, Lion Air dan Merpati yang juga bisa bisa dipesan di pegipegi.com.Reservasi perjalanan online pegipegi bisa dilakukan dengan metode pembayaran yang universal dan bisa dilakukan oleh semua wisatawan baik mereka yang datang dari lokal maupun internasional. Adapun pembayaran yang disediakan adalah e-banking, melalui ATM, serta kartu debit atau kartu kredit yang kesemuanya bisa dilakukan tanpa adanya pungutan biaya transaksional.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.106 | 0.051 |
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".