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Record W2233939267 · doi:10.5039/agrária.v9i4.3732

Funções de pedotransferência para retenção de água e condutividade hidráulica em solo submetido a subsolagem - DOI:10.5039/agraria.v9i4a3732

2015· article· pt· W2233939267 on OpenAlexaboutno aff
Joabe Martins de Souza, Robson Bonomo, Fábio Ribeiro Pires, Diego Zancanella Bonomo

Bibliographic record

VenueRevista Brasileira de Ciências Agrárias (Agrária) Brazilian Journal of Agricultural Sciences · 2015
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsnot available
Fundersnot available
KeywordsPedotransfer functionHydraulic conductivityWater retentionSoil scienceBulk densityWater potentialEnvironmental scienceSoil waterWater retention curve

Abstract

fetched live from OpenAlex

This experiment aimed to develop pedotransfer functions, based on soil physical-hydric attributes, to estimate the water retention and hydraulic conductivity. The experiment was carried out in area with a Conilon ( Coffea canephora Pierre) coffee crop irrigated and subjected to subsoiling in the row of planting. Undeformed samples were collected on the row (P1) and inter row (P2) of the crop from the layer 0 to 0.80 m, to determine the water retention curve in the soil, and soil conductivity by using Guelph permeameter. The pedotransfer functions showed underestimates for the potentials 0, -500 and -1500 kPa and -6, -10, -33 and -100 kPa, respectively in P1 and P2. In P2 the average relative error for the potential percentage was 8.42%, which is higher than the P1 (4.87%), resulting in higher error in the estimates of height of water stored in the soil. The water retention curve for the subsoiling soil may be estimated with error less than 5%, by clay, total porosity, macroporosity, microporosity and soil density attributes, and the hydraulic conductivity by soil clay fraction. For non-subsoiling soil, the retention curve may be estimated with error less than 9%, by the total pore volume and macro and micropores and the hydraulic conductivity by the coarse sand fraction.

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 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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.005
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0050.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.284
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueRevista Brasileira de Ciências Agrárias (Agrária) Brazilian Journal of Agricultural SciencesSame topicSoil Management and Crop YieldFrench-language works237,207