Nilai taksonomi ciri anatomi daun genus Schoutenia Korth. (Malvaceae subfam. Brownlowioideae)
Bibliographic record
Abstract
Kajian anatomi dan mikromorfologi daun telah dijalankan ke atas lima takson dalam genus Schoutenia Korth. (Malvaceae subfam. Brownlowioideae). Lima takson yang dipilih dalam kajian ini ialah S. kunstleri, S. leprosula, S. accrescens subsp. accrescens, S. accrescens subsp. borneensis dan S. accrescens subsp. stellata. Kajian anatomi melibatkan kaedah hirisan dengan mikrotom gelongsor pada bahagian petiol, lamina, tulang daun dan tepi daun, kaedah penjernihan lamina dan kaedah siatan epidermis daun, penjernihan dengan larutan peluntur, pewarnaan dengan Safranin dan Alcian Blue, pelekapan Canada Balsam dan cerapan bawah mikroskop cahaya. Kajian mikromorfologi melibatkan kaedah pendehidratan, titik pengeringan kritikal, saduran emas dan cerapan bawah mikroskop imbasan elektron. Objektif kajian ialah untuk melihat nilai taksonomi ciri anatomi dan mikromorfologi daun dalam genus yang dikaji. Hasil kajian menunjukkan terdapat sembilan ciri sepunya, tujuh ciri variasi yang boleh digunakan untuk pembezaan spesies dan dua ciri diagnostik yang boleh digunakan untuk pengecaman spesies. Ciri tersebut ialah corak hiasan kutikel pada S. kunstleri dan juga kehadiran sel kolenkima lamela pada S. accrescens subsp. stellata. Hasil kajian menunjukkan ciri anatomi serta mikromorfologi daun dalam genus Schoutenia mempunyai nilai taksonomi terutama dalam pembezaan dan pengecaman pada peringkat spesies dan subspesies.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".