PROFIL PROGNASI WAJAH BEBERAPA POPULASI DUNIA [Prognation Profile of World Population Faces]
Bibliographic record
Abstract
The face is one of the major variables in determining the biological characteristics of a population in the identification effort of human skeletal remains. This is not only important in the field of forensic anthropology but also the field of bioarchaeology. The purpose of this study is to describe the variation of facial angle in some of the world population. The method applied is anthropometry. The study material is the skull of nine world populations of Europe, North Africa, Subsahara Africa, South America, Inuit, Australomelanesia, Indonesia, Polynesia and China. The results showed that among the population tested, Australomelanesoid, Polynesian, Indonesian and African Subsahara populations had a prognathic face both on the even face, as well as the alveolar and facial projection. In contrast, the population groups of China, Europe, Inuit and North Africa are population groups that have faces of orthognath. ABSTRAKWajah adalah salah satu variabel utama dalam menentukan ciri biologis suatu populasi pada usaha identifikasi sisa rangka manusia. Hal ini tidak hanya panting dalam bidang antropologi forensik tetapi juga bidang bioarkeologi. Tujuan penelitian ini adalah untuk mendeskripsikan variasi sudut wajah pada beberapa populasi dunia. Metode yang diterapkan adalah antropometri. Bahan penelitian adalah tengkorak dari sembilan populasi dunia yaitu populasi Eropa, Afrika Utara, Afrika Subsahara, Amerika Selatan, Inuit, Australomelanesia, Indonesia, Polinesia dan China. Hasil penelitian menunjukkan bahwa diantara populasi yang diuji, populasi Australomelanesoid, Polinesia, Indonesia dan Afrika Subsahara memiliki wajah yang prognath baik pada bagian wajah genap, maupun bagian alveolar serta proyeksi wajah. Sebaliknya kelompok populasi China, Eropa, Inuit dan Afrika Utara adalah kelompok populasi yang memiliki wajah orthognath.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".