Bibliographic record
Abstract
Each year the New Phytologist Trust is proud to award the New Phytologist Tansley Medal to an individual in the early stages of his or her career who has made an outstanding contribution to plant science. We are delighted to announce that the recipient of the 2016 Tansley Medal is Dr Etienne Laliberté of the University of Montreal, Canada. Etienne's research focusses on the impact of ecological interactions among plants, microbes and soils on communities and ecosystems. To find out more about Etienne and his contributions to understanding community effects of plant–soil–microbe interactions, please see his Profile in this issue of the journal (Laliberté, 2017a, pp. 1580–1581), or listen to an interview with him, available at: https://soundcloud.com/new-phytologist/interview-with-etienne-laliberte-winner-tansley-medal-2016/s-t0hib. Etienne Laliberté's Tansley insight is titled ‘Below-ground frontiers in trait-based plant ecology’ (Laliberté, 2017b, pp. 1597–1603). In his Tansley insight Etienne notes that despite advances in plant biology using trait-based approaches, below-ground approaches have been overlooked. Etienne proposes to redress this by highlighting six ‘below-ground frontiers’ in trait-based plant ecology, with particular emphasis on traits that govern soil nutrient acquisition. These six frontiers are intended to help focus research efforts to maximize the potential of trait-based ecology, and to ultimately enhance predictive capacity across ecological scales. We offer our warmest congratulations to Etienne and his fellow finalists, and we wish them continued success. We look forward to following their future careers. The judging panel for the 2016 Tansley Medal was comprised of the following New Phytologist Editors: Prof. Amy Austin, Prof. Liam Dolan, Prof. Alistair Hetherington, Prof. Elena Kramer and Prof. Natalia Requena.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.396 | 0.322 |
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".