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Record W2947625063 · doi:10.5539/jas.v11n8p196

Multivariate Geospatial Feature of the Soil Attributes of Archaeological Dark Earth in Novo Aripuanã, AM

2019· article· en· W2947625063 on OpenAlexvenueno aff
José Maurício da Cunha, Milton César Costa Campos, Alan Ferreira Leite de Lima, Elilson Gomes de Brito Filho, Douglas Marcelo Pinheiro da Silva, Fernando Gomes de Souza, Lucivânia Izidoro da Silva, Maria Clécia Gomes Sales, Ivanildo Amorim de Oliveira

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicAmazonian Archaeology and Ethnohistory
Canadian institutionsnot available
Fundersnot available
KeywordsGeostatisticsSoil scienceMultivariate statisticsEnvironmental scienceSoil testEcosystemPasturePhysical geographySoil carbonGeographySoil waterGeologyForestrySpatial variabilityMathematicsEcologyBiologyStatistics

Abstract

fetched live from OpenAlex

Changes in natural ecosystems for the use and management of soil can have negative consequences, favoring the appearance of areas susceptible to physical degradation. This work aimed to evaluate changes on the soil properties in Archaeological Dark Earth environments preserved under pigeon pea cultivation and pasture, using multivariate geostatistics technique. Sampling meshes were delimited with regular spacings with 88 sample points per mesh and then georeferenced. Soil samples and volumetric rings were collected in the layers 0.0-0.05 m, 0.05-0.10 m and 0.10-0.20 m, for the determinations of the physical attributes and soil organic carbon. The main components main components 1 (MC1) and main components 2 (MC2) were characterized by attributes related to the stability of the aggregates (geometric average diameter (GAD), weighted average diameter (WAD) and aggregate classes) and the related soil structure taxes, respectively, with a variability of soil attributes under forest influenced by values above the mean for both main components. Land use under pigeon pea little influenced the variability of the main components, presenting values of the attributes related to these components near the mean values, while the soil under pasture promoted influence only to the attributes related to main components 2 (MC2).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.593
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.218
Teacher spread0.201 · 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 teacher head, 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

Citations1
Published2019
Admission routes1
Has abstractyes

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