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Record W3114953239 · doi:10.1139/cjss-2020-0098

Soil phosphorus fractionation after co-applying biochar and paper mill biosolids

2020· article· en· W3114953239 on OpenAlexaffvenue
Noura Ziadi, Xiangru Zhang, Bernard Gagnon, Eric Manirakiza

Bibliographic record

VenueCanadian Journal of Soil Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiocharLoamBiosolidsSoil waterChemistryFertilizerIncubationPhosphorusFractionationEnvironmental chemistryAgronomyAmendmentNutrientEnvironmental sciencePyrolysisSoil scienceEnvironmental engineeringBiology

Abstract

fetched live from OpenAlex

In recent decades, there has been a growing interest in the recycling of organic materials such as paper mill biosolids (PB) and biochar for use as soil amendments. However, the benefits of co-application of PB and biochar and its effects on soil phosphorus (P) availability remain unknown. An incubation study was conducted on two acidic soils to assess the effect of two PB types (2.5% w/w) co-applied with three rates (0%, 2.5%, and 5% w/w) of pine (Pinus strobus L.) biochar on soil P fractions. An unfertilized control and a mineral NP fertilizer were used as a reference. Soil P fractions were determined by Hedley procedure after 2 and 16 wk of incubation. Material fractionation indicated that the PB containing the highest total P and the lowest Al content had the highest proportion of labile P, whereas most P in the biochar was in a stable form. The incubation study revealed that the P-rich PB increased P availability in both soils to a level comparable to mineral fertilizer at the end of the incubation. The addition of biochar to PB, however, did not affect soil P availability, but the highest rate induced a conversion of P fixed to Al and Fe oxides towards recalcitrant forms, particularly in the sandy loam soil. We conclude that co-applying biochar and PB could be more beneficial than application biochar alone and soils amended with such a mixture would be expected to release part of their P slowly over a longer period of time.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalmedium
models agreeAgreement compares identical category sets and study designs across arms.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.206
Teacher spread0.197 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2020
Admission routes2
Has abstractyes

Explore more

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