MétaCan
Menu
Back to cohort
Record W3008508067 · doi:10.2136/sssaspecpub60.c3

Soil and Water Conservation Advances in the Semiarid Northern Great Plains

2010· book-chapter· en· W3008508067 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSSSA special publication series · 2010
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSoil conservationEnvironmental scienceAgricultureDryland farmingAgroforestryPrecipitationResource (disambiguation)CroppingWater resourcesGeographyEcology

Abstract

fetched live from OpenAlex

This chapter deals with the semiarid Northern Great Plains (NGP), which includes parts of Montana, North Dakota, South Dakota, Wyoming, Nebraska, Alberta, and Saskatchewan. It discusses and illustrates how advances in soil and water conservation technology have evolved to improve precipitation use and to develop sustainable agricultural systems that are resilient for the NGP. The chapter presents an example to demonstrate that more intensive agriculture is often more sustainable than low input agriculture. Recent dryland cropping systems research efforts in the NGP have focused on the elimination of summer fallow, with its negative effects on soil quality and its inefficient soil water storage. To more efficiently use precipitation and energy from the sun in the future, people will need to develop techniques that not only control soil erosion and conserve water, but enhance the soil resource.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.875

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)0.0010.000

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 head0.012
GPT teacher head0.198
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