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Record W1995772874 · doi:10.4141/s01-003

N<sub>2</sub> fixation by soybeans grown with different levels of mineral nitrogen, and the fertilizer replacement value for a following crop

2002· article· en· W1995772874 on OpenAlexfundvenueno aff
M. Goss, Amarílis de Varennes, Paul Smith, J. A. Ferguson

Bibliographic record

VenueCanadian Journal of Soil Science · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsnot available
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsFertilizerAgronomyNitrogen fixationNitrogenMineralization (soil science)Yield (engineering)CropChemistryGrain yieldMathematicsBiology

Abstract

fetched live from OpenAlex

A field experiment was established to study the impact of added mineral N on the prediction of N 2 fixation by soybean, and the consequences for the nature of any N credit that might be used to modify fertilizer recommendations to a following non-fixing crop. Nodulating and non-nodulating isolin es of soybean were grown with five rates of N fertilizer, and in a second year corn was grown in the same plots and its yield compared with a response curve. Yield, total N content, amount of N derived from soil, and fertilizer utilization of the nodulating isoline of soybean were not affected by fertilizer N. In contrast, mineral N inhibited nodulation and led to a decrease in the amount of N fixed. The balance of N in the soil was more negative for lower levels of applied N, but by the following spring the amount of mineral N in the soil was the same in all plots. The yield of corn was greater in the plots that had grown nodulating soybean than the non-nodulating isoline. The N fertilizer replacement value of 25 (8 kg N ha -1 resulted from a greater amount of root residues in the nodulating soybean, together with a C:N ratio that would favour faster mineralization than in the non-nodulating isoline. Key words: Corn, mineral N, N credit, fixation, soybean

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.729

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 studies0.0000.001
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 head0.017
GPT teacher head0.198
Teacher spread0.182 · 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 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

Citations37
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Soil ScienceSame topicLegume Nitrogen Fixing SymbiosisFrench-language works237,207