Bibliographic record
Abstract
This document provides an overview of Canadian intellectual property (IP) law with a focus on its relevance to protecting Geospatial Data, information and products. "Geospatial data" is understood as raw data, such as geographic coordinates. "Geographic information" (GI) is understood as geographic data placed in context (for example, data about the location of mineral resources). "Geospatial data products" is understood to mean the form in which the data is expressed, and can include databases, maps, charts, photographs or other documents or products. IP is generally understood as having three main areas: copyright, patent and trademark. Other categories include industrial design law, the protection of integrated circuit topographies, and the protection of plant varieties. Confidential information or trade secrets are often considered to be a form of IP protected at common or civil law, or in equity. The focus in this paper is on confidential information, copyright, trademarks and patents, although copyright is the predominant basis for the protection of geographic data and related information products.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.070 | 0.012 |
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".