Information-rich sensors by assembly: a review on the use of macrocyclic hosts in the context of complex chemical systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Host-based sensors that offer cross-reactivity to analytes can be valuable tools in the detection and differentiation of biologically relevant molecules. This review Feature Article provides a foundational background in developing macrocyclic host-based systems that harness chemical complexity to achieve sensing in biologically relevant solutions. We highlight our own contributions along with select examples from others, covering noncovalent self-assemblies, salt tolerant synthetic designs, and current multicomponent systems approaches to host-based sensing and differentiation. We emphasize our personal perspective on building complex systems, as an evolving strategy to obtaining emergent information-rich outputs that surpass the performance of conventional host-based sensor pairs. These recent developments are at the frontier of the field, involving more challenging sensing tasks, including the detection and identification of highly similar analytes, biomacromolecules, and complex mixtures.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it