Data for 'Evolutionary history and root trait coordination predict nutrient strategy in tropical legume trees': Fabaceae trait data
Bibliographic record
Abstract
This file contains raw trait data for a greenhouse pot experiment of 22 species of tropical and subtropical Fabaceae trees and shrubs, published as Marcellus et al. (2024) ''Evolutionary history and root trait coordination predict nutrient strategy in tropical legume trees' in New Phytologist. Data include growth and biomass (leaf, stem, nodule, thorn, coarse and fine root), leaf traits (specific leaf area, foliar P, A max), symbiotic traits (acetylene reduction activity, arbuscular mycorrhizal colonisation) and root traits (specific root length, diameter, tissue density, root N, root C, root 13C, root 15N and phosphatse activity). Species include seven non-fixers: Adenanthera pavonina, Caesalpinia pulcherrima, Coulteria velutina, Delonix regia, Parkinsonia aculeata, Parkinsonia africana, Parkinsonia florida and 15 fixers: Acacia baileyana, Acacia confusa, Acaciam dealbata, Acacia mearnsii, Acacia saligna, Albizia julibrissin, Albizia lebbeck, Enterolobium cyclocarpum, Leucaena leucocephala, Prosopis chilensis, Prosopis juliflora, Samanea saman, Senegalia senegal, Vachellia erioloba and Vachellia farnesiana.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".