Analisa Rencana Overlay Landas Pacu Bandar Udara Iskandar Pangkalan Bun, Terhadap Equivalent Single Wheel Load (ESWL) Pesawat Boeing 737-900 ER
Bibliographic record
Abstract
Bandar udara Iskandar yang terus berupaya meningkatkan kualitas pelayanan penerbangan bagi masyarakat pengguna, berencana melakukan pengembangan fasilitas landas pacu dari 1.850 meter menjadi 2.250 meter. Pemanjangan fasilitas landas pacu sepanjang 350 meter ini diharapkan agar pesawat udara berbadan lebar dapat mendarat di bandar udara Iskandar yang saat ini baru dapat didarati oleh pesawat dengan tipe 737500. Analisa rencana overlay landas pacu bandar udara Iskandar Pangkalan Bun, terhadap Equivalent Single Whell Load (ESWL) pesawat Boeing 737-900ER ini dilakukan dengan tujuan untuk mengetahui ketebalan rencana lapisan perkerasan landas pacu yang akan di overlay terhadap equivalent single wheel load (ESWL) pesawat hoeing 737-900 ER. Sementara itu, perurnusan masalah dari pengkajian ini adalah apakah rencana tebal perkerasan overlay fasilitas landas pacu di Bandar Udara Pangkalan Bun telah memenuhi persyaratan untuk dapat didarati pesawat tipe Boeing 737-900 ER. Bandar Udara Iskandar pangkalan Bun akan melakukan overlay setebal 7,5 cm. sehingga flexible pavement yang semula setebal 80 cm akan menjadi setebal 87,5 cm. tetapi, dari hasil perhitungan terlihat bahwa tebal pavement minimal adalah 88 cm. oleh sebab itu terdapat selisih tebal lapisan perkerasan hasil perhitungan dengan rencana sebesar 0.25 cm.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".