Some Notable Discoveries in Organosilicon Chemistry: Proceedings of the History and Retrospective Session of the 34th Organosilicon Symposium (2001)
Bibliographic record
Abstract
The 34th Organosilicon Symposium at White Plains, NY, in 2001 featured a History and Retrospective Session, during which invited speakers from academic and industrial laboratories recounted the path to some significant 20th century discoveries in organosilicon chemistry. The Si=C Story: The Way it Happened, Adrian G. Brook (University of Toronto) The Discovery of Stable Disilenes and Silylenes, Robert West (University of Wisconsin) Yellow Fever: The Story Behind the Synthesis of Germasilenes, Kim M. Baines (University of Western Ontario) Direct Synthesis of Tris(dimethylamino)silane, William B. Herdle (OSi Specialties, formerly of Union Carbide Corporation) Discovery of Tin and Phosphorus Effects on the Direct Synthesis of Methylchlorosilanes, Larry H. Wood (Dow Corning Corporation) Discovery of Methylchlorosilylene (CH3SiCl) as a Key Intermediate in the Direct Synthesis of Dimethyldichlorosilane ((CH3)2SiCl2), Kenrick M. Lewis (OSi Specialties, formerly of Union Carbide Corporation) The First Platinum-Catalyzed Hydrosilylation With Supported Platinum Catalysts, George H. Wagner (Retired, formerly of Union Carbide Corporation) The Discovery of Silicone Surfactants for Polyurethane Foam, Bernard Kanner (Retired, formerly of Union Carbide Corporation) The Discovery of Silane Coupling Agents, Bernard Kanner (Retired, formerly of Union Carbide Corporation)
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".