Bibliographic record
Abstract
Self-assembly and directed-assembly are two very important aspects of supramolecular chemistry. As a young postgraduate student working in Canada with Tom Fyles my introduction to Supramolecular Chemistry was through the self-assembly of phospholipid membranes to form vesicles for which we were developing unimolecular and self-assembling transporter molecules. The next stage of my development as a scientist was in Japan with Seiji Shinkai where in a "Eureka" moment, the boronic acid templating unit (directed-assembly) of Wulff was combined with photoinduced electron transfer systems pioneered by De Silva. The result was a turn-on fluorescence sensor for saccharides; this simple result has continued to fuel my research to the present day. Throughout my career as well as assembling molecules, I have enjoyed bringing together researchers in order to develop collaborative networks. This is where molecules meet people resulting in assemblies worth more than the individual "molecule" or "researcher". My role in developing networks with Japan was rewarded by the award of a Daiwa-Adrian Prize in 2013 and I was recently rewarded for developing networks with China with an Inaugural CASE Prize in 2015.
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.
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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".