MétaCan
Menu
Back to cohort

Variabilidade espacial da condutividade hidráulica e da infiltração da água no solo

2009· article· pt· W2052465222 on OpenAlexaboutno aff
Clementina Scherpinski, Miguel Ángel Uribe-Opazo, Márcio Antônio Vilas Boas, Sílvio C. Sampaio, Jerry Adriani Johann

Bibliographic record

VenueActa Scientiarum Agronomy · 2009
Typearticle
Languagept
FieldEnvironmental Science
TopicSoil Geostatistics and Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsPermeameterGeostatisticsSpatial variabilityHydraulic conductivitySoil scienceInfiltration (HVAC)Environmental scienceSpatial correlationVariogramHydrology (agriculture)Soil waterMathematicsGeologyGeographyGeotechnical engineeringKrigingStatisticsMeteorology

Abstract

fetched live from OpenAlex

When cultivated areas are used with intense agricultural production, the soil presents spatial and temporal alterations in its hydrophysical attributes so that the economical viability of the agricultural production depends on those attributes, requiring detailed studies consequently about the spatial variability of the soil. Thus, the objective of this work was to evaluate the spatial variability of the saturated hydraulic conductivity and water infiltration in the soil, in an area of 20 ha, characterized by intensive grain production, was used a grid of 50 x 50 m grating, using the Guelph Permeameter. In the spatial variability analyses, geostatistics methods were used. It was concluded that the hydrophysical attributes studied presented structures of spatial dependence and behaved proportionally, but did not show spatial correlation in the 50 m density of studied.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.247
Teacher spread0.230 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueActa Scientiarum AgronomySame topicSoil Geostatistics and MappingFrench-language works237,207