Potency, Patenting and Preformation: The Patentability of Totipotent Cells in Canada
Bibliographic record
Abstract
The Canadian Intellectual Property Office’s (CIPO) publication entitled, Office Practice Regarding the Patentability of Fertilized Eggs, Stem Cells and Tissues, is examined with respect to the patentability of totipotent cells. It is conjectured that its position against the patentability of totipotent cells is based upon a mistaken view of animal development and stem cell differentiation called “genetic preformationism.” This view holds that the DNA in a totipotent cell is the sole determinant of development and differentiation so that a totipotent cell containing the DNA of a higher life form is a higher life form. It ignores the fact that modern biologists have recognised an increasingly important role for non-genetic, environmental factors in both animal development and stem cell differentiation. Given that the CIPO’s views on development and differentiation are incorrect and the process of developing the Notice lacked transparency, justification and intelligibility, it cannot justifiably reject an application for a patent on a fertilised egg or totipotent stem cell on the basis of the reasons given in the Office Practice Regarding the Patentability of Fertilized Eggs, Stem Cells and Tissues. This paper suggests that there are legal, practical and scientific limits of the ability of the CIPO, like other patent offices, to apply patent legislation wisely to fundamentally new technologies.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.018 | 0.015 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".