Expanding the scope of molecular self-organization studies through temperature control at the solution/solid interface
Bibliographic record
Abstract
Professor Federico Rosei holds the Canada Research Chair in Nanostructured Organic and InorganicMaterials, Institut National de la Recherche Scientifique, Energie, Materiaux et Telecommunications, Universite du Quebec, Varennes (QC) Canada. He received M.Sc. and Ph.D. degrees from the University of Rome ‘La Sapienza’ in 1996 and 2001, respectively. Dr. Rosei’s research interests focus on the properties of nanostructured materials, and on how to control their size, shape, composition, stability, and positioning when grown on suitable substrates. He has extensive experience in fabricating, processing, and characterizing inorganic, organic, and biocompatible nanomaterials. He has published 110 articles in prestigious international journals (including Science, Advanced Materials, Angewandte Chemie Int. Ed., Journal of the American Chemical Society, Nanoletters, Small, Physical Review Letters,Applied Physics Letters, Physical Review B, etc.), has been invited to speak at over 120 international conferences and has given over 130 seminars and colloquia in 33 countries on all inhabited continents. His publications have been cited over 2000 times and his H index is 24. He has received several awards, including the FW Bessel Award from the Alexander vonHumboldt Foundation, the FQRNT Strategic Professorship (2002–07), the TanChin Tuan visiting Fellowship (NTU 2008), the Senior Gledden Visiting Fellowship (UWA 2009), Professor at Large at UWA (2010–12), a Marie Curie Post-Doctoral Fellowship from the European Union (2001) and a Canada Research Chair since 2003 (renewed in 2008 for a second 5-year term). He is Member of the Sigma Xi Society, Fellow of the Institute of Nanotechnology and of the Institute of Physics.
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 | 0.001 |
| 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) | 0.000 | 0.000 |
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 teacher head, 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".