Adapting the CATIMO grass model to meadow bromegrass grown in western Canada
Bibliographic record
Abstract
Bonesmo, H., Baron, V. S., Young, D., Bélanger, G. and Jing, Q. 2014. Adapting the CATIMO grass model to meadow bromegrass grown in western Canada. Can. J. Plant Sci. 94: 61-71. The Canadian Timothy Model (CATIMO) simulates the growth and nutritive value of timothy grown in eastern and western Canada, Norway, and Finland, but has not been parameterized for meadow bromegrass (Bromus riparius Rehm.) grown under Canadian prairie conditions. We parameterized and evaluated the CATIMO model to simulate the dry matter (DM) yield and N concentration of meadow bromegrass grown in western Canada with data from sequential sampling in primary growth and regrowth from two field experiments for a total of 5 yr of observation. Primary growth DM yield was simulated well [R2=0.95; normalized root mean square error (NRMSE) =16%; model simulation efficiency (EF)=0.93]. Simulations of the regrowth DM yield (R2=0.49, NRMSE=39%, EF=0.47) were not as successful as that of the primary growth, but they were within expected ranges for regrowth DM yields in western Canada. Forage N concentration was poorly simulated in primary growth (R2=0.32, NRMSE=38%, EF=-0.95) and regrowth (R2=0.27, NRMSE=30%, EF=-2.43). Plant-available soil moisture down to 30 cm was simulated well (R2=0.74, NRMSE=19%, EF=0.50). The parameterized model for meadow bromegrass expands the use of the CATIMO model to drier geographical areas where timothy may not be common, and it represents a first attempt to provide DM yield assessment of meadow bromegrass under Canadian Prairie conditions for whole-farm modeling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".