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Record W2801744502 · doi:10.31274/icm-180809-935

Increasing the Odds of a Profitable Yield Response to Foliar Fungicide Application on Corn

2008· article· en· W2801744502 on OpenAlexaboutno aff
Alison E. Robertson, John M. Shriver, Ken Pecinovsky

Bibliographic record

VenueProceedings of the Integrated Crop Management Conference · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Residue Analysis and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsFungicideYield (engineering)OddsAgronomyBiologyMathematicsStatisticsLogistic regressionMaterials science

Abstract

fetched live from OpenAlex

During the 2007 growing season, approximately 3 million acres of corn were sprayed with a foliar fungicide. Yield responses due to a fungicide application varied widely. Data compiled from university trials in 12 Corn Belt states and Ontario, Canada in 2007 showed an average yield response of 3 bu/acre to applications of corn fungicides (Bradley, 2008). Among the industries from on-farm trials, BASF reported an average yield increase of 12 to 16 bu/acre, Bayer CropScience an average yield increase of about 10 bu/acre and Syngenta an average yield increase of 15 to 20 bu/acre (Farm Industry News, Feb 15, 2008).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.180

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.025
GPT teacher head0.218
Teacher spread0.193 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

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