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Record W2499405167 · doi:10.4148/2378-5977.1233

Soybean: Evaluation of Inoculation

2016· article· en· W2499405167 on OpenAlexaboutno aff
Ignacio A. Ciampitti, Eric Adee, Jennifer Kimball, Gabriela Inveninato Carmona

Bibliographic record

VenueKansas Agricultural Experiment Station Research Reports · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsnot available
Fundersnot available
KeywordsInoculationAcreCropBushelAgronomyGrowing seasonBiologyYield (engineering)Horticulture

Abstract

fetched live from OpenAlex

A soybean crop can obtain up to 50 to 75% of its nitrogen (N) requirements from the air when the biological fixation is effectively established (Pedersen, 2007). The overall objective of this project was to quantify the response to inoculation for soybean in a field without previous history of this crop. Following this rationale, a field study was conducted during the 2015 growing season at Ottawa (east central Kansas). The treatments consisted in five different N management approaches: non-inoculated, inoculated × 1, inoculated × 2, inoculated × 3 and non-inoculated but fertilized with 300 lb N per acre as the main N source. The study was planted in an area without soybean history, the grain yield ranged from 26 to 29 bushels per acre. Greater yields were recorded when a double inoculation rate was applied (× 2), while lowest yield was related to the non-inoculated scenario. However, statistically, treatments did not present any significant yield difference. In summary, further research will be performed to be more conclusive as related to the best management approach for N in soybeans when first planted in fields without previous history of this crop.

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)0.003
metaresearch head score (Gemma)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.098
GPT teacher head0.359
Teacher spread0.261 · 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.

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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

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