Statistical mechanics of solvophobic aggregation: Additive and cooperative effects
Bibliographic record
Abstract
Effects of possible non-pairwise-additive interactions on solvophobic aggregation are analyzed. A simple lattice model of binary solution with attractive solute-solute interactions is introduced to delineate the role of multiple-body effects in solute clustering and aggregation. Additive (noncooperative), cooperative, and anti-cooperative intersolute interactions are modeled by multiple-solute potentials that are respectively equal to, more favorable than, and less favorable than the sum of pairwise solute interactions. Under appropriate conditions, pairwise additive interactions and even interactions with significant anti-cooperativity can lead to aggregation and demixing. Cooperative interactions are not necessary for solute aggregation. Similarities and differences between solute aggregation and hydrophobic collapse of proteinlike heteropolymers are investigated. On average, heteropolymer collapse transitions as a function of solvophobic composition are significantly less sharp than the corresponding solute aggregation transitions. This difference is seen as a direct consequence of chain connectivity constraints.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".