SEBARAN HABITAT ANGGREK ALAM DI TAMAN NASIONAL LORE LINDU
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Keanekaragaman jenis anggrek alam di Taman Nasional Lore Lindu belum banyak diungkapkan, namun berbagai habitatnya terancam kelestariannya karena aktivitas manusia. Dalam buku ini membahas mengenai keanekaragaman jenis anggrek pada berbagai tipe hutan yang berbeda ketinggian, serta faktor lingkungan dan jenis tumbuhan inangnya. Penelitian dalam buku ini dilakukan dari bulan Januari sampai Juni 2019 di empat tempat yang berbeda tipe hutannya berdasarkan elevasi, yaitu Bobo (hutan dataran rendah), Kamarora (hutan pegunungan bawah), Kalimpa’a (hutan pegunungan), dan Rorekautimbu (hutan pegunungan atas) dalam kawasan Taman Nasional Lore Lindu (TNLL). Hasil penelitian dalam buku ini menunjukan bahwa terdapat 45 jenis anggrek (26 marga), yang terdiri dari 36 bersifat epifit dan 9 jenis terrestrial dengan total 242 individu. Pada hutan dataran rendah dan hutan pegunungan atas ditemukan 22 jenis, hutan pegunungan bawah 12 jenis dan pada hutan pegunungan 16 jenis anggrek. Indek keaneragaman jenis (H’) di semua lokasi tergolong rendah nilainya < 1. Kemerataan jenis (e) anggrek pada empat lokasi tergolong sedang pada hutan dataran rendah 0,908, hutan pegunungan rendah 0,731.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it