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Record W2296531609 · doi:10.5539/jas.v8n4p76

Crop Water Production Functions—A Review of Available Mathematical Method

2016· article· en· W2296531609 on OpenAlexvenueno aff
Manijeh Mahmoudzadeh Varzi

Bibliographic record

VenueJournal of Agricultural Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
Fundersnot available
KeywordsEvapotranspirationAgricultural engineeringYield (engineering)Context (archaeology)Production (economics)CropCrop productionMathematicsCrop yieldAgronomyAgricultureEngineeringGeographyEconomicsPhysicsEcologyBiology

Abstract

fetched live from OpenAlex

Crop water production function is the relationship between obtained marketable yield and the total amount of water used by plant through evapotranspiration. Different mathematical expressions have been derived from field experiments to predict yield knowing water use. Such expressions provide a powerful tool in water allocation optimization. However these functions are commonly confused with the relationship between available water and crop yield. This paper reviews functions that describe crop water production, the context they can be used for, and their strength and weakness.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.007
Science and technology studies0.0000.001
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.004

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 head0.037
GPT teacher head0.264
Teacher spread0.228 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations30
Published2016
Admission routes1
Has abstractyes

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