Quantifying the Contribution of Plant Breeders’Rights and Transgenic Varieties to Canola Yields: Evidence from Manitoba
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.
Bibliographic record
Abstract
Canola yield functions that account for plant breeders’rights, changes in technology, measures of varietal diversity and environmental conditions are estimated for the province of Manitoba for the period 1995–2001. Various measures are employed to estimate the effect of plant breeders’rights (PBR) on canola yields. Panel data models, which allow for differences in behavior over cross‐sectional units at the same point in time as well as differences in behavior over time for a given cross‐sectional unit, are used for the analysis. The performance of canola yield response functions are superior with random effects models. The adoption of transgenic varieties and varieties qualifying for PBR are positively associated with increasing yields. The policy implication of this study is that a greater commitment of public funds to fundamental research may be necessary to complement the applied research that private companies are undertaking in producing finished varieties.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it