TINGKAT ERROR PETENIS PUTRA YANG MENGIKUTI \nKEJUARAAN NASIONAL TENIS JUNIOR \nNEW ARMADA CUP XX TAHUN 2016
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui seberapa besar tingkat error \npetenis putra yang mengikuti kejuaraan nasional tenis junior new armada cup XX \ntahun 2016. \nMetode penelitian ini menggunakan metode deskriptif kuantitatif. Populasi \npenelitian adalah atlet tenis lapangan putra yang bertanding dalam Kejuaraan \nNasional Tenis Junior New Armada Cup XX tahun 2016. Sampel penelitian \nadalah atlet Kelompok Umur 16 tahun putra pada quarter final, semi final dan \nfinal. Seluruh data penelitian diperoleh melalui observasi dengan menggunakan \nUnforced Error Analysis Sheet. Teknik analisis data yang digunakan adalah \nanalisis statistik deskriptif persentase. \nHasil penelitian menunjukkan bahwa tingkat error petenis putra yang \nmengikuti Kejuaraan Nasional Tenis Junior New Armada Cup XX tahun 2016 \npada permainan tunggal jumlah persentase error smash 3.85%, groundstroke \n53.62%, Volley 20.40% dan service 22,13%. Sedangkan untuk permainan ganda \njumlah persentase error smash 2.93%, groundstroke 31.31%, volley 40.06% dan \nservice 25.69%.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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; both teacher heads agree on what is shown here.
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".