Bibliographic record
Abstract
What do water filters, wind turbine blades, and semiconductor polishing pads have in common? Polymer chemistry—and big contributions from Alaaeddin Alsbaiee. To get that kind of breadth at 38 years old, you have to start early. “I’ve liked chemistry since I was a kid. I had some test tubes and Erlenmeyers in my bedroom,” Alsbaiee says. The tools were gifts from his uncle, an organic chemist who worked for the food and drink company Nestlé. The 1999 Nobel Prize in Chemistry, awarded to Ahmed Zewail—the first person from the Arabic-speaking world to win the honor—galvanized Alsbaiee’s desire to become a scientist. So when Alsbaiee started at Syria’s Damascus University the next year, he picked a chemistry major. As his education took him around the world from Syria to Saudi Arabia, Canada, and the US, he developed a systematic approach to science that his peers say has led to a lot
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) | 0.000 | 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".