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Record W4306893261 · doi:10.21203/rs.3.rs-2174390/v1

Total Iron and Different Iron Forms Contents Affecting by Soil Characteristics in Vertisols, SE Turkey

2022· preprint· en· W4306893261 on OpenAlexaff
Tuba Çınar Büyükkılıç, Ali̇ Seyrek, Asuman Büyükkılıç Yanardağ, İbrahim Halil Yanardağ, A. R. Mermut, Ángel Faz Cano

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsVertisolOrganic matterSiltChemistryLimeTotal organic carbonSoil organic matterEnvironmental chemistryRhizosphereSoil scienceSoil testMineralogySoil waterEnvironmental scienceMetallurgyGeologyMaterials science

Abstract

fetched live from OpenAlex

<title>Abstract</title> Iron (Fe) in the soil is a very important element for agricultural applications and the development of plants, which have different forms. The presence of Fe in the rhizosphere is controlled by the activity of Fe forms in the soil and the microorganisms and surrounding root-soil interaction of plants and roots. The objectives of this study were to identify, and to examine their interaction with soil properties in vertisols. The results showed that; Fe<sub>T</sub> contents ranged from 1.17 and 47.71 g kg<sup>-1</sup>, mean 13.81 g kg<sup>-1</sup> › Fe<sub>D</sub> contents 0.18 to 17.85 g kg<sup>-1</sup> and mean 7.23 g kg<sup>-1</sup> › Fe<sub>O</sub> contents 0.01–0.31 g kg<sup>-1</sup> mean 0.18 g kg<sup>-1</sup> › Fe<sub>DTPA</sub> contents 0.00–0.17 g kg<sup>-1</sup> mean 0.04 g kg<sup>-1</sup> › Fe<sub>P</sub> contents 0.00–0.02 g kg<sup>-1</sup> mean 0.01 g kg<sup>-1</sup>. Clay-silt fractions and organic matter had a very powerful impression on Fe forms distribution. Fe<sub>D</sub>, Fe<sub>DTPA</sub>, Fe<sub>O</sub> ve Fe<sub>P</sub> had low quantities. This is thought to be due to insufficient rainfall and some soil characteristics (including high pH, low organic matter, clay texture, and high lime content), as iron is not easily dissolved in the soil. There was a very important relation between clay content, organic matter, silt fractions, and Fe forms in the studied area. There was a positive correlation between soil organic carbon and DTPA-extractable Fe. There was a negative correlation between DTPA-extractable Fe and soil pH, also calcium carbonate content. When total Fe was rised, clay-silt content and cation exchange capacity (CEC) increased in the soil profiles. Especially in Zone 3 has more Fe and Fe contents, the results showed that; There was a very good balance between the different Fe fractions and soil properties. Zone 3 had more total iron contents than the other zones, because of their soil properties. Fe bound by organic sites, water-soluble plus exchangeable Fe and Fe were adsorbed onto oxides (amorphous surfaces) and were positively correlated with the DTPA-extractable Fe.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
Research integrity0.0000.002
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 head0.046
GPT teacher head0.317
Teacher spread0.272 · 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
Published2022
Admission routes1
Has abstractyes

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