Generation of Monodisperse Particles by Using Microfluidics: Control over Size, Shape, and Composition
Bibliographic record
Abstract
Wir versäumten, in unserer Veröffentlichung die interessanten und wesentlichen Arbeiten von Gañán-Calvo et al. zu zitieren: A. M. Gañán-Calvo, Phys. Rev. Lett. 1998, 80, 285; A. M. Gañán-Calvo, J. M. Gordillo, Phys. Rev. Lett. 2001, 87, 274 501; I. G. Loscertales, A. Barrero, I. Guerrero, R. Cortijo, M. Marquez, A. M. Gañán-Calvo, Science 2002, 295, 1695. Des Weiteren möchten wir den interessierten Leser auf weitere wichtige Berichte hinweisen, z. B.: I. Cohen, H. Li, J. L. Hougland, M. Mrksich, S. R. Nagel, Science 2001, 292, 265; S. Sugiura, M. Nakajima, H. Itou, M. Seki, Macromol. Rapid. Commun. 2001, 22, 773; T. Nisisako, T. Torii, T. Higuchi, Chem. Eng. J. 2004, 101, 23. Auch wenn die Einzelheiten der Fluidphysik und die spezifischen Anwendungen in unserer Arbeit von denen in den genannten Berichten abweichen, illustrieren doch die Vorgängerarbeiten dieser Autoren den Wert von strömungsfokussierenden Systemen bei der Erzeugung hoch einheitlicher Tropfen und das Potenzial für die Verwendung dieser Tropfen in den Materialwissenschaften. Nach dem Einreichen unserer Arbeit erschienen zwei weitere Veröffentlichungen, die den Einsatz von Mikrofluidikkanälen für die In-situ-Erzeugung anisotroper polymerer Partikel dokumentieren: W. Jeong, J. Kim, S. Kim, S. Lee, G. Mensing, D. J. Beebe, Lab Chip 2004, 4, 576; D. Dendukuri, K. Tsoi, T. A. Hatton, P. S. Doyle, Langmuir 2005, 21, 2113.
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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) | 0.000 | 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".