Design of [2]rotaxane through image threshold segmentation of electrostatic potential image
Bibliographic record
Abstract
An electrostatic potential (ESP)-based image segmentation method has been used to estimate the ability of proton donation and acceptance involved in ring-rod recognition. The relative binding strength of [2]rotaxane has also been further estimated from the difference of the characteristic image-segmentation derived ESP between proton donor and proton acceptor. The size and electrostatic compatibility criteria are introduced to guide the design of interlocked [2]rotaxane. A library of 75 thermodynamically stable [2]rotaxane candidates has been generated, including 16 experimentally known systems. The theoretical results for 16 experimentally known [2]rotaxanes are in good agreement with both the experimental association constants and density functional theory-calculated binding energies. Our ESP-based image segmentation model is also applicable to the tristable [2]rotaxane molecular shuttle as well as [1]rotaxane with self-inclusion function, indicating this simple method is generic in the field of constructing other supramolecular architectures formed with donor/acceptor molecular recognition. © 2016 Wiley Periodicals, Inc.
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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) | 0.001 | 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 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".