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Record W3126272959 · doi:10.1016/j.gecco.2021.e01480

Field decomposition of Bt-506 maize leaves and its effect on collembola in the black soil region of Northeast China

2021· article· en· W3126272959 on OpenAlexfundno aff
Baifeng Wang, Junqi Yin, Fengci Wu, Zhilei Jiang, Xinyuan Song

Bibliographic record

VenueGlobal Ecology and Conservation · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsnot available
FundersMuséum National d'Histoire NaturelleNational Natural Science Foundation of ChinaUniversity of Saskatchewan
KeywordsLitterAgronomyNitrogenDecompositionAnimal scienceBiologyAbundance (ecology)Plant litterBotanyChemistryEcologyEcosystem

Abstract

fetched live from OpenAlex

The litters from Bt maize are always plowed into the soil after harvest. To clarify whether the decomposition rate of Bt litters and the nontarget soil fauna in the litters are influenced by Bt protein or the other organic matter, the leaf pieces of Bt-506, its near isoline Zheng 58 and a local type Zhengdan 958 were put into litterbags and buried into the field in Northeast China. Then, the Bt protein content of Bt-506 litters, the nonstructural carbohydrate and total nitrogen contents, and decomposition rates of all leaf litters and the collembolan communities in these litters were investigated after a period of buried time. There was 43.5 ng/g Bt protein remained in Bt-506 litters at the end of the experiment, when the Bt-506 litters had been kept in field for decomposition for 7 months. Except for Bt protein, none of the other investigated indexes were significantly different between Bt-506 and Zheng 58 at any sampling time. However, when compared with Zhengdan 958, the leaf litters of Bt-506 and Zheng 58 contained less nonstructural carbohydrate but more total nitrogen, and had lower decomposition rate, lower collembolan abundance and Shannon-Wiener index at some sampling times. Correlation analysis showed that the leaf litter decomposition rate and the collembolan abundance in litters were significantly correlated with the nonstructural carbohydrate content and the total nitrogen content of maize litters on May 20 (after buried in field for 6 months), and neither collembolan abundance nor leaf litter decomposition rate was correlated with maize type at any sampling time. In sum, Bt protein did not affect the decomposition rate of leaf litters and the collembolan community in litters; the differences of leaf litter decomposition rate and the collembolan community in litters between Bt-506, Zheng 58 and Zhengdan 958 were probably resulted from the different contents of nonstructural carbohydrate and total nitrogen in the leaf litters.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.278

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)0.0000.000

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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 teacher head, 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

Citations1
Published2021
Admission routes1
Has abstractyes

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