MétaCan
Menu
Back to cohort
Record W3161265407 · doi:10.1139/cjss2010-058

Overview of Mollisols in the world: Distribution, land use and management

2012· article· en· W3161265407 on OpenAlexaboutno aff
Xiaobing Liu, C. Lee Burras, Yuriy Kravchenko, Artigas Durán, Ted Huffman, Héctor José María Morrás, Guillermo Alberto Studdert, Xingyi Zhang, Richard M. Cruse, Xiaohui Yuan

Bibliographic record

VenueIowa State University Digital Repository (Iowa State University) · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMollisolDistribution (mathematics)Environmental scienceLand useGeographyPhysical geographySoil scienceEcologyBiologySoil waterMathematics

Abstract

fetched live from OpenAlex

Liu, X., Burras, C. L., Kravchenko, Y. S., Duran, A., Huffman, T., Morras, H., Studdert, G., Zhang, X., Cruse, R. M. and Yuan, X. 2012. Overview of Mollisols in the world: Distribution, land use and management. Can. J. Soil Sci. 92: 383-402. Mollisols - a.k.a., Black Soils or Prairie Soils - make up about 916 million ha, which is 7% of the world's ice-free land surface. Their distribution strongly correlates with native prairie ecosystems, but is not limited to them. They are most prevalent in the mid-latitudes of North America, Eurasia, and South America. In North America, they cover 200 million ha of the United States, more than 40 million ha of Canada and 50 million ha of Mexico. Across Eurasia they cover around 450 million ha, extending from the western 148 million ha in southern Russia and 34 million ha in Ukraine to the eastern 35 million ha in northeast China. They are common to South America's Argentina and Uruguay, covering about 89 million and 13 million ha, respectively. Mollisols are often recognized as inherently productive and fertile soils. They are extensively and intensively farmed, and increasingly dedicated to cereals production, which needs significant inputs of fertilizers and tillage. Mollisols are also important soils in pasture, range and forage systems. Thus, it is not surprising that these soils are prone to soil erosion, dehumification (loss of stable aggregates and organic matter) and are suffering from anthropogenic soil acidity. Therefore, soil scientists from all of the world's Mollisols regions are concerned about the sustainability of some of current trends in land use and agricultural practices. These same scientists recommend increasing the acreage under minimum or restricted tillage, returning plant residues and adding organic amendments such as animal manure to maintain or increase soil organic matter content, and more systematic use of chemical amendments such as agricultural limestone to replenish soil calcium reserves.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.013
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.202
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations58
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueIowa State University Digital Repository (Iowa State University)Same topicMarine Bivalve and Aquaculture StudiesFrench-language works237,207