PENGETAHUAN JENIS LAPANGAN FUTSAL YANG DIGUNAKAN DI INDONESIA PADA MAHASISWA OLAHRAGA
Bibliographic record
Abstract
Futsal is a giant ball game modified on the field, and the rules are to be played in any place the size of a quarter of a football field; futsal is known as small football, which has the attraction to play it very enthusiastically. Many fields can be used to play futsal, such as cement which is often found in the area and plastic interlocks that have been used in every city that has a standard field. However, some fields are commonly used but not commonly used, such as standarlex, synthetic grass, vinyl and wood parquet. Knowledge of this type of field needs to be known as an introduction to the field and for adapting the type of shoe suitable for play. The presentation of material about knowledge of futsal field types is carried out by lecture, and question and answer description of futsal field types is the method in this PKM. The results of this PKM are expected to know about the futsal fields used in Indonesia.
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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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.009 |
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".