Adjustable temperature sensor with double thermoresponsiveness based on the aggregation property of binary diblock copolymers
Bibliographic record
Abstract
Abstract This article presents a new and promising way to design a temperature sensor, which is based on the micellization or aggregation behavior of binary diblock copolymers of poly(ethylene glycol)‐b‐poly(N‐isopropylacrylamide) (PEG‐b‐PNIPAM) and poly(ethylene glycol)‐b‐poly(4‐vinylpyridine) (PEG‐b‐P(4‐VP)). The temperature sensor presents both a lower critical response temperature (LCRT) and an upper critical response temperature (UCRT), where the thermoreversible aggregating of PEG‐b‐P(4‐VP) and H2SO4 is used to control the LCRT, and the thermoreversible micellization of PEG‐b‐PNIPAM is used to control the UCRT. Furthermore, the LCRT can be altered by changing the H2SO4 concentration, and the UCRT can be adjusted by altering the PEG‐b‐PNIPAM concentration. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 3144–3148, 2006
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".