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Record W2766007552 · doi:10.25077/js.4.1.5-9.2007

DEGRADASI LAHAN PADA KEBUN CAMPURAN DAN TEGALAN DI KABUPATEN DHARMASRAYA

2007· article· en· W2766007552 on OpenAlexaff
Syafrimen Yasin, Gusnidar Gusnidar, Dedy Iskandar

Bibliographic record

VenueJurnal Solum · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsImperataUltisolRangelandEnvironmental scienceForestrySoil testSoil carbonSoil fertilityAgronomyGeographyAgroforestrySoil waterSoil scienceBiology

Abstract

fetched live from OpenAlex

A research conducted in Sungai Rumbai, Dharmasraya Regency and in Soil Laboratory Andalas university was aimed to evaluate soil fertility status on the depth below 0-20 cm from several land use types , especially under Mixed Garden and annual cultivated dryland soil.  Soil samples were taken on Ultisol at 0-8% slope (late-waving soil surface).  Land use types evaluated were forest, annual cultivated dryland, bush land, rangeland covered by Imperata cylindrica and mixed garden.  Composite soil samples for soil chemical analysis were taken on the 0-20 cm soil depth with four replications, and 5 drillings for each replication.  Undisturbed soil samples by using sample ring were used to analyze sol bulk volume.  The data resulted were compared to the criteria and were statistically tested using Analysis of Variance and then were continued by LSD at 5% level.  From the results of analyses could be concluded that land use  for mixed garden had the higher Organic Carbon (OC) content and the lower bulk volume (BV) than those for annual cultivated dryland soil.Key Words: Degradasi Lahan, Kebun Campuran, Tegalan

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.317

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)0.0000.000

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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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
Published2007
Admission routes1
Has abstractyes

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