Bibliographic record
Abstract
We prove that Carlos is a Canadian, and document some important contribution of Carlos to the growth of mathematical epidemiology in Canada.Carlos is a Canadian.Here is a proof: Canadian nationality law specifies that Canadian citizenship is typically obtained by birth in Canada, birth abroad when at least one parent is a Canadian citizen [1].Carlos is a mathematical son of a Canadian [2], Professor Fred Brauer, completing the proof.Carlos is a modern citizen and has contributed substantially to the growth and strength of Canadian research and training in mathematical biology and mathematical epidemiology.He has been a much sought after speaker for many, if not all, mathematical epidemiology meetings, workshops and summer schools organized by Canadians.In my memory, he has never said no to any invitation from his fellow Canadian organizers, despite the huge temperature gradient between Phoenix and a typical Canadian city in the winter (Of course, being a Canadian, Carlos is constitutionally unable to say "no" to any invitation to participate in any Canadian event).Carlos gave a lecture "Social Structure" at the 2004 MITACS-MSRI-PIMS Special Program on Infectious Diseases [3] held in Banff.This lecture attracted not only 43 students, but a couple of (Canadian!)deer to Max Bell 159, the lecture room of the Banff International Research Station.Carlos was very proud of this.He interrupted his lecture and welcomed the special audience.However, the deer came a bit late, they did not register and hence had to stand outside during the entire lecture.Carlos was also an instructor for the 2006 Fields-MITACS Summer School on Mathematical Modelling of Infectious Diseases and he delivered his public lecture "Epidemiological Approaches and its Applications to Public Security" at the Fields Institute.Carlos was a member of the Scientific Advisory Board of the Banff International Research Station during 2008Station during -2011 [4] [4], and he was partially responsible for the outbreaks of disease modelling events held at the Station.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 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; 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".