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Record W3201284550 · doi:10.1139/cjss-2020-0113

Effect of biochar applications on soil phosphorus availability under different soil moisture levels

2021· article· en· W3201284550 on OpenAlexvenueno aff
Yuxin Li, Haixiao Li, Xueqiang Lu

Bibliographic record

VenueCanadian Journal of Soil Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsBiocharFertilizerPhosphorusMoistureWater contentEnvironmental scienceAgronomyFractionationNutrientSoil scienceChemistryGeologyPyrolysisBiology

Abstract

fetched live from OpenAlex

Soil moisture level is crucial to soil phosphorus (P) availability; however, there is no quantitative research on the relation between soil P availability and moisture level. In addition, biochar application could also alter soil P availability at different moisture levels. In this study, a 16 d soil incubation experiment was conducted at a laboratory scale to analyze the effects of soil moisture and P fertilization regimes (P-laden biochar fertilizer and conventional mineral P fertilizer) on soil P availability and fractionation. The results showed that soil P availability was positively correlated with soil moisture level (Pearson coefficients ranged from 0.46 to 0.91). High moisture level would lead to less amount of P in readily available fractions under P-laden biochar application. However, even with less P in readily available fractions, P-laden biochar could maintain soil P availability (117.7 mg P·m −2 ) at a similar level as the conventional P fertilizer (116.1 mg P·m −2 ).

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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 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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Soil Science→Same topicSoil Carbon and Nitrogen Dynamics→French-language works237,207→