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Diversidad de macroinvertebrados acuáticos y su importancia en el ecosistemas dulceacuícolas del Río Seco, Tortí, Panamá

2025· article· es· W4410039569 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista Semilla del Este · 2025
Typearticle
Languagees
FieldEnvironmental Science
TopicWater Resource Management and Quality
Canadian institutionsTetra Tech (Canada)Ontario Tech University
Fundersnot available
KeywordsPanamaGeographyEcologyBiology

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.008
GPT teacher head0.257
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it