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Record W2377575696

Comparison of Spatial Interpolation Methods for Soil Available Kalium

2006· article· en· W2377575696 on OpenAlex
Lei Zhang

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

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Agricultural Sciences
Canadian institutionsScience North
Fundersnot available
KeywordsSoil nutrientsInterpolation (computer graphics)Multivariate interpolationSampling (signal processing)Spline (mechanical)Environmental scienceSoil scienceNutrientHydrology (agriculture)MathematicsStatisticsComputer scienceSoil waterGeologyBilinear interpolationChemistry
DOInot available

Abstract

fetched live from OpenAlex

Continuous soil nutrient data is the basic data of soil information system,soil nutrient spatial interpolation study becomes very important because it can affect the data reliability of soil nutrient data straightly.In this study,soil available kalium data,Zhouzhi county,Shaanxi province,is sampled and got the interpolation map of available kalium with OK,IDW,Spline and TSA according to interpolating sampling points.The cross validation results showed that OK is the best which used spherical model in these methods;although Spline and IDW could also produce fair and reasonable results,both of them were sensitive to sampling density,interpolation result appeared large prediction errors in those regions which had exiguous sampling points.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.312
Teacher spread0.291 · 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

Quick stats

Citations4
Published2006
Admission routes1
Has abstractyes

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