Osteologi Ikan Keureling (Tor tambroides)
Bibliographic record
Abstract
ndonesia merupakan negara dengan keanekaragaman ikan yang tinggi, salah satunya ikan yang berasal dari genus Tor. Terdapat 40 spesies ikan Tor di Asia, empat spesies diantaranya hidup di Indonesia yaitu Tor tambroides, Tor douronensis, Tor tambra, dan Tor soro. Saat ini kajian terhadap ikan dari genus ini masih terbatas pada bidang ekologi dan upaya domestikasi. Upaya untuk mengkaji lebih jauh terkait morfologi lebih khususnya osteologi ikan keureling masih belum banyak dilakukan.Kajian morfologi skeleton ikan merupakan bagian penting dalam memahami sistematika ikan, diantaranya untuk mempelajari hubungan taksonomi dan logenetik antar species ikan. Disamping itu, pengetahuan berkenaan dengan deskripsi morfologi skeleton suatu species ikan sangat dibutuhkan sebagai langkah preventif dalam menganalisis abnormalitas sistem skeleton.Buku ini mengulas tentang klasi kasi dan ekologi ikan keureling, metode pembuatan preparat tulang ikan keureling, sistem osteologi ikan, morfologi tulang kepala ikan keureling, morfologi tulang belakang ikan keureling, dan morfologi tulang anggota gerak ikan keureling. Disamping itu, buku ini diharapkan dapat menghadirkan konsistensi dalam hal penyajian nomenklatur tulang penyusun rangka, mengidenti kasi perbedaan osteologi antar spesies ikan, dan memahami hubungan taksonomik dan logenetik antarspesies ikan.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".