Diversidad de macroinvertebrados acuáticos y su importancia en el ecosistemas dulceacuícolas del Río Seco, Tortí, Panamá
Bibliographic record
Abstract
Con el objetivo de determinar la diversidad de macroinvertebrados y su importancia en el ecositema dulceacuícola de ri?o Seco, se dividio? el ri?o en a?rea de amortiguamiento (sitio 1 y 2) y a?rea de impacto directo (sitio 3), siendo monitoreadas entre los meses de julio y septiembre de 2019. Las muestras fueron tomadas de hojarascas, piedras y palos a las orillas del ri?o o sumergidas en e?l y, adema?s, se utilizó la red Surber. Los ejemplares capturados fueron transportados al laboratorio en bolsas herme?ticas e identificados con claves taxono?micas. Se recolectaron un total de 706 especi?menes de macroinvertebrados, distribuidas en 10 o?rdenes y 28 familias. Las ordenes ma?s abundantes fueron Ephemeroptera (262), Coleoptera (167), Hemiptera (120), Diptera (71) y Trichoptera (57). Para determinar la diversidad (H ?), equitatividad (J ?) y dominancia (D ?), se utilizaron los i?ndices de Shannon-Wiener, Pielou, Simpson los resultados evidenciaron una diversidad media, una buena mezcla de especies, con una distribución relativamente equitativa entre ellas, lo que es favorable para la biodiversidad del ecosistema y el protocolo SVAP arrojo? un resultado de 8.27 indicando que el a?rea estudiada de río Seco tienen una calidad buena.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".