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Record W2138744445

석회암 유래 토양에서의 물의 이동특성과 토양 입자 및 유기물과의 관계에 따른 Pedo-Transfer Function의 결정

2009· article· ko· W2138744445 on OpenAlexaboutno aff
허승오, 정강호, 손연규, 하상건, 김정규

Bibliographic record

Venue한국토양비료학회지 · 2009
Typearticle
Languageko
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterInfiltrometerInfiltration (HVAC)Soil scienceGeologySoil texturePermeameterSiltWater contentHydraulic conductivityMineralogyGeotechnical engineeringGeomorphologyGeography
DOInot available

Abstract

fetched live from OpenAlex

Soils originated from limestone, located at the southern part of Kangwon province and Jecheon, Danyang of Chungbuk province are mainly composed of fine texture, have different properties from soils originated from granite and granite gneiss, especially for water movement. This study was conducted for making PTF(Pedo-Transfer Function) for Kfs(field saturaton hydraulic conductivity) estimation, and for investigating the relation between soil particle distribution and the infiltration and percolation rate in soils originated from limestone. Soils used for the experiment were 6 soils of Gwarim, Mosan, Jangseong, Maji, Anmi and Pyongan series. Infiltration and percolation rate for the soil were measured by a disc tension infiltrometer and a Guelph permeameter, respectively. The particle size distribution and organic matter content of the soils were analyzed. Kfs was not related with sand, silt, clay, and organic mattrer (OM) content because of forest soils which contained high gravel, pebble, and cobble content, and O layer with high OM content. After Mosan soil series and O layer of Gwarim series were excluded for the data analysis, Kfs was explained as a linear function with sand and clay content and a exponential function with OM content. As a result, the PTF equation was obtained as Kfs=-4.20558+0.479706*(S) +0.023187*exp(1.829*OM) (R 2 =0.6558 * ).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.016
GPT teacher head0.201
Teacher spread0.185 · 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venue한국토양비료학회지Same topicAgriculture, Soil, Plant ScienceFrench-language works237,207