GENETIC VARIATION AMONG Pinus patula POPULATIONS ALONG AN ALTITUDINAL GRADIENT. TWO ENVIRONMENT NURSERY TESTS VARIACIÓN GENÉTICA ENTRE POBLACIONES DE Pinus patula EN UN GRADIENTE ALTITUDINAL. ENSAYO DE VIVERO EN DOS AMBIENTES
Bibliographic record
Abstract
SUMMARY Aiming to determine if there is genetic differentiation among Pinus patula Schiede et Chamizo populations along an altitudinal gradient and for quantifying the genotype x environment interaction, 13 Pinus patula populations were sampled from forests of the Native Indian Community of Ixtlan de Juarez, Oaxaca, state of Mexico, along an altitudinal gradient (2400 m to 3000 m), cones being collected on groups of trees on every 50 m of altitudinal step). Seedlings were grown in tree pots in two different environments: a shadehouse located at Ixtlan de Juarez, and in a greenhouse and then in a shadehouse situated at Quebec, Canada. Total seedling height was measured at 6-months of age in both locations. Results indicated that populations differed significantly (P = 0.025), but there was no significant genotype x environment interaction (P = 0.426; B type genetic correlation = 0.93). Population from 2650 m (middle altitude) exhibited the best height. Although not definitive, our study suggests the presence of a weak altitudinal pattern of variation in seedling height, where populations originating of mid-altitudes exhibit the highest growth potential while populations from the upper and lower altitudinal extremes exhibit the lowest growth potential. Index works:
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".