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Record W3210760401 · doi:10.21608/eajbsh.2021.196892

Evaluation of Some Soil Tests to Extract Many of The Available Micronutrients in The Egyptian Soils

2021· article· en· W3210760401 on OpenAlexaboutno aff
Mohamed Wafaa, Gad Hanan, Noori Saleh Mena

Bibliographic record

VenueEgyptian Academic Journal of Biological Sciences, H. Botany/Egyptian Academic Journal of Biological Sciences, H. Botany · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsCalcareousExtraction (chemistry)Soil testSoil waterMicronutrientCalcareous soilsEnvironmental chemistryEnvironmental scienceChemistrySoil scienceGeologyChromatography

Abstract

fetched live from OpenAlex

Three extractions were used to assess the availability of micronutrients in different soil collections. The suitability of some extractions under the conditions of Egyptian soils will be discussed. Three extraction methods (Mehlic 3, Soltanpour and Kelowna) were used for the determination of available Fe, Zn, Mn, Cu and B content of the soil samples (sand,calcareous and clay) during 2020 season. Surface soil samples (0-30 cm) were collected from three sites of Al Boston area in the new Nobaria, Governorate, Egypt, during 2020 season. From each selected plot, ten points were selected in a zig-zag path. The results revealed that the highest values of available Fe, Zn and Cu were given with the extraction solution of Soltanpour, while the highest values of available Mn and B were given with the extraction solution of Mehlic 3. On the other hand, the results showed that clay soil recorded the maximum available Fe, Zn, Mn and Cu, while calcareous soil recorded the maximum available boron content. The interaction between different extraction methods and soil samples was highly significant during 2020 season.

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)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.101
GPT teacher head0.334
Teacher spread0.232 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEgyptian Academic Journal of Biological Sciences, H. Botany/Egyptian Academic Journal of Biological Sciences, H. Botany →Same topicHeavy metals in environment→French-language works237,207→