Taxonomic significance of seed characters and SDS-PAGE analysis in the classification of Ericaceae
Bibliographic record
Abstract
Classification of nineteen taxa, belong to ten genera of family Ericaceae are studied. The study based on macro-, micro-morphological characters of seeds and SDS-PAGE analysis techniques. The phenetic relationships of the studied taxa were expressed by UPGMA-clustering method using NTSYS-pc 2.2 software. The UPGMA phenogram based on 47 characters revealed the separation of two major clusters (A) and (B). Group (A) subdivided into two sub ordinary clusters (AC), expressed subfamily Vaccinoideae, and (AD) which expressed together with main group (B) subfamily Ericoideae. The studied genera are distributed equally between these two subfamilies. Vaccinoideae is represented by five tribes: Vaccinieae, Gaultherieae, Oxydendreae, Lyonieae and Andromedeae. Ericoideae is separated as two clades representing two tribes: (AD) Phyllodoceae and (B) Rhodoreae. The produced hierarchical taxonomic arrangement typically matches the traditional classifications of the family. Clustering of Menziesia pilosa with Rhododendron menziesii in near distance with all Rhododendron taxa confirmed the placement of both genera under tribe Rhodoreae, and supports the transfer of genus Menziesia to be nested in Rhododendron as recommended by some recent cladistics analyses of DNA data.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 0.000 |
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".