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Soil Instrumental Methods

2015· other· en· W4248196697 on OpenAlex
Adam Gillespie, E. G. Gregorich, Bobbi L. Helgason, Derek Peak

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

VenueEncyclopedia of Analytical Chemistry · 2015
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsUniversity of SaskatchewanAgriculture and Agri-Food CanadaCanadian Light Source (Canada)
Fundersnot available
KeywordsEnvironmental scienceSoil waterSoil organic matterOrganic matterEarth scienceSoil ecologySoil scienceSoil biodiversityEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Abstract Soils serve as an interface between aquatic, atmospheric, and terrestrial ecosystems. In this capacity, the soil provides important functions such as supporting plant and animal life, regulating the flows of energy, nutrients, and water, and providing a sink and source for greenhouse gases. Soil is composed of interacting mineral, organic, water, and air components, all of which are transformed and cycled by a rich and diverse microbial population. Knowledge of the chemical, physical, and biological properties of soil can only be fully obtained using a suite of analytical methods. This article describes the basic concepts and approaches to laboratory analysis of soil materials to address a wide range of disciplines, standard methodologies, and research techniques, with an emphasis on modern instrumental methods. This article covers modern instrumental methods for the analysis of soil chemical properties, soil organic matter (SOM), and soil biology and includes detailed information on spectroscopic and spectrometric methods.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.031
Threshold uncertainty score0.993

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)0.0080.000

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 head0.015
GPT teacher head0.271
Teacher spread0.256 · 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