Techopia EY With Kyle Bratz -Audio
Bibliographic record
Abstract
Kyle Braatz is on a mission to change health care. That's a lofty goal, but the company he leads and co-founded is growing in leaps and bounds with revenues exceeding $600 million. In September, Braatz was named the 2022 CEO of the Year by Ottawa Business Journal and the Ottawa Board of Trade.Over almost 12 years, Braatz has taken the company from an idea he and business partners Brad Dyment and Chris Wise hashed out in his living room to a multinational enterprise that provides nutritional supplements and other natural health-care products as well as treatment plans to more than five million patients.Now with 900 employees, about 300 located in Ottawa, Fullscript raised US$240 million in equity financing - the biggest such funding haul in the nation's capital since the dot-com boom in the early 2000s - and acquired one of its biggest competitors.[CKEBLOCK]adslotposition1_content_embed[/CKEBLOCK]There is no stopping the University of Ottawa alumnus, who is the 23rd recipient of CEO of the Year, joining a who's who of local business executives, including Shopify co-founder Tobi Lütke, Calian Group's Kevin Ford and Kinaxis CEO John Sicard.CEO of the Year is sponsored by Boyden, a specialist in executive recruitment with offices in Ottawa.For more about Braatz, read this profile in Ottawa Business Journal: https://obj.ca/article/local/fullscript-co-founder-kyle-braatz-named-ottawas-2022-ceo-year
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.437 | 0.004 |
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".