MétaCan
Menu
← Back to cohort
Record W2897613089

Second-year decomposition and nutrient release characteristics of ten annual crop residues in south-central Saskatchewan, Canada

2018· article· en· W2897613089 on OpenAlexfundaboutno aff
R.D. Hangs, J.J. Schoenau

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNutrientCropDecompositionEnvironmental scienceGeographyForestryEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

MATERIALS & METHODS• Post-harvest residues were collected in the fall of 2015 from farm fields in Saskatchewan, dried to a constant weight, and a 5-g subsample placed in a polyethylene screen bag (20 × 20 cm; 1 mm mesh) and stapled closed.Additional subsamples of the original residues (i.e., time = 0) were analysed for their nitrogen (N), phosphorus (P), potassium (K), and sulfur (S) contents.• Prior to snowfall, the litter bags (n = 4) were placed on the soil surface of a farm field in south-central Saskatchewan and arranged in a completely randomized design.• The soil is an Orthic Brown Chernozem with pH 7.6 and 20 mg/kg extractable NO 3 -N, 10 P, 300 K, and 25 S in the 0-15 cm depth.• Four collection times were chosen: the spring of 2016 (six months) and the fall of 2016 (1 year), 2017 (2 years; reported here), and 2018 (3 years).• The residual litter was dried to a constant weight, weighed to determine mass loss, and analysed for its N, P, K, and S contents.• Meteorological data (air temperature, rainfall, relative humidity, wind speed, and snow depth), along with soil temp/moisture (0-60 cm), are being collected using an adjacent MET station. OBJECTIVE• Quantify the mass loss and changes in nutrient content of decomposing harvest residues from a variety of annual cereal, pulse, and oilseed crops grown in Saskatchewan: barley, wheat, oats, field pea, lentil, soybean, faba bean, canola, flax, and hemp.• Post-harvest plant residues represent a significant addition of carbon (C) and nutrients to soil; however, limited work has been done to investigate their fate within low disturbance agricultural systems, where these residues are not incorporated into the soil.• Quantifying these dynamics will improve our understanding of how different crop residues impact C sequestration and nutrient cycling, along with providing data for the development and validation of agroecosystem C and nutrient biogeochemical cycling models.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.003
GPT teacher head0.186
Teacher spread0.183 · 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 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
Published2018
Admission routes2
Has abstractyes

Explore more

Same topicSoil and Water Nutrient Dynamics→French-language works237,207→