Determinants of the grant lag and the surrender lag of horticultural crop plant breeders’ rights applications: Survival analysis with competing risks
Bibliographic record
Abstract
Abstract Obtaining a Plant Breeders’ Rights (PBR) certificate provides horticultural institutions the exclusive right to produce and reproduce new varieties, which directly motivate new plant variety innovations. This study investigates how the grant and surrender lag of PBR certificates is influenced by the crop type and applicant characteristics using the Canadian Food Inspection Agency horticultural crop PBR application data for the period 1992–2014. Results from the Fine and Gray subdistribution hazard model reveal that the grant lag and surrender lag of Canadian PBR applications significantly vary by the country of origin of the applicant, whether the applicant is a public institution or private company/individual, horticultural crop types, and the decades when applications are filed. The policy implications of the results provide useful information to stakeholders of the Canadian Plant Breeders’ Rights System regarding how the lifespan of PBRs is influenced by crop type and applicant characteristics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".