Michèle Prévost Honored With 2016 A.P. Black Award
Bibliographic record
Abstract
The A.P. Black Research Award, established in 1967 in honor of Alvin Percy Black, is given on an as‐deserved basis to recognize a researcher for outstanding research contributions to water science and water supply rendered over an appreciable period of time. Dr. Michèle Prévost from École Polytechnique de Montréal received the 2016 A.P. Black Award during the AWWA Annual Conference & Exposition (ACE) in Chicago, Ill., on June 20. Prévost has been a professor and the industrial research chair in drinking water for the Natural Sciences and Engineering Research Council (NSERC) of Canada in the Department of Civil Engineering of Polytechnique Montréal since 1992. She is an internationally renowned expert in the treatment and distribution of drinking water, with a demonstrated ability to produce usable research results and transfer them to end users. Kenneth Mercer, editor‐in‐chief of Journal AWWA, spoke with Prévost to learn about her trajectory in water research, her advice for young professionals, and her dedication to public health. The transcript of the interview that follows has been edited for clarity and length.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.122 | 0.053 |
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".