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Record W2069043569 · doi:10.2134/agronj2002.3370

Timothy Yield and Nutritive Value by the CATIMO Model

2002· article· en· W2069043569 on OpenAlex
Helge Bonesmo, Gilles Bélanger

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgronomy Journal · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsForageDry matterLeaf area indexInterceptionYield (engineering)LimitingAgronomyGrowth modelDynamic simulation modelMathematicsModel validationCalibrationEnvironmental scienceAnimal scienceBiologyStatisticsEcologyPhysics

Abstract

fetched live from OpenAlex

Mechanistic simulation models can assist in developing recommendations to optimize yield and nutritive value and in understanding the complex interaction among plant growth, nutritive value, and environmental conditions. In this paper, we present the growth and N concentration modules of an integrated model [CATIMO (Canadian Timothy Model)] of timothy ( Phleum pratense L.) primary growth and nutritive value. This growth model features radiation interception and use efficiency, leaf and stem growth, leaf senescence, and a N function based on the critical N concentration of whole plants. Model parameters were calibrated to key model attributes: leaf area index (LAI); forage N concentration; and leaf, stem, and forage dry matter (DM) yields. Calibration measurements were taken weekly on timothy primary growth in four different years at one location (Fredericton, NB, Canada). Overall, the model satisfactorily fitted the measured values with root mean square errors of 32.8, 42.0, and 65.9 g m −2 leaf, stem, and forage DM yield, respectively. The model tended to underestimate stem DM yield at the end of the primary growth cycle, overestimate forage N concentration under nonlimiting N conditions, and underestimate N concentration under limiting N conditions. The model satisfactorily fitted LAI in 3 of 4 yr. Summary statistics of the calibration indicate a successful description of growth and development of the essential plant components required for modeling digestibility.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.029
GPT teacher head0.195
Teacher spread0.166 · 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