Bibliographic record
Abstract
The following discussion will examine the utility requirement for patentability in the context of EST patents. Part I will provide background information regarding the utility requirement under patent law and will explain why it has been difficult to apply to ESTs. Part II will briefly examine how other jurisdictions, in particular the United States, have addressed the difficul- ties associated with applying the current utility require- ment to biological materials, in particular ESTs. Part III will look at how Canadian courts have interpreted and applied the utility requirement for patentability, and will suggest that ESTs have sufficient value to the scientific community to satisfy this requirement. In addition, it will examine how the doctrine of sound prediction may allow patent protection to be extended beyond the simple EST nucleotide sequence. This article will conclude by suggesting two reasons why the utility criterion for patentability has proven difficult to apply to human genetic materials.\nThe patenting of human genetic materials, including ESTs, raises a number of concerns apart from the question of whether they meet the utility requirement under patent legislation. Not only are there legal concerns in terms of whether such ‘‘inventions’’ are patentable subject-matter and whether they satisfy the requirements of novelty and non-obviousness, but there are also important moral concerns. While all of these issues are clearly related and not completely separable, an examination of their intersection is beyond the scope of this article.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".