Cuantificación de hongos micorrícicos en muestras de suelo en plantaciones de Tabebuia rosea y Cordia alliodora
Bibliographic record
Abstract
The tropical grounds show great restrictions for tree production after they have been used and over-exploited by man. A strategy to increase the levels of production is based on the fertilization according to the requirements of the trees. As mycorrhization is a biological low cost alternative that can contribute to the success of the reforestation, we wanted to establish how it was possible to favor the surviving and growth of arboreal species in green houses by means of the quantification of mycorrhizal fungi using ground samples in the species Tabebuia rosea and Cordia alliodora in different localities from Costa Rica, Central America.Samples in ten different sites were analyzed and the quantification of spores was made by sifting. The percentage of colonization by roots was considered at microscopic observation by roots according to methodology of Sieverding. The results obtained in this investigation concluded that from the variety of the present sorts of Micorrizas Vesiculo Arbusculares in the ground sample those that demonstrated better behavior with Tabebuia rosea and Cordia alliodora were Glomus sp. and Gigaspora sp. In addition, to obtain a greater growth and development of the trees, it is necessary to favor the mycorrhizal population in the plants within their first days of birth.
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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 | 0.000 | 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".