The 2-oxo-3,3,5,5-tetramethylcyclopentanecarboxylic acid ketoenol system in aqueous solution Generation of the enol by flash photolytic Wolff rearrangement of 2-diazo-4,4,6,6-tetramethylcyclohexane-1,3-dione followed by hydration of the acylketene thus formed
Bibliographic record
Abstract
Flash photolysis of 2-diazo-4,4,6,6-tetramethylcyclohexane-1,3-dione in aqueous solution produced 2-oxo-3,3,5,5-tetramethylcyclopentylideneketene, which underwent hydration to the enol of 2-oxo-3,3,5,5-tetramethylcyclo pentanecarboxylic acid; the enol then isomerized to the keto form of the acid. Rates of hydration of the ketene and rates of ketonization of the enol were measured in perchloric acid, sodium hydroxide, and buffer solutions, and rate profiles were constructed. Rates of enolization of 2-oxo-3,3,5,5-tetramethylcyclopentanecarboyxlic acid were also measured, using bromine to scavenge the enol as it formed, and rates of enolization and ketonization were then combined to give the ketoenol equilibrium constant pKE = 1.65. This and other results are discussed in comparison with the behavior of the unmethylated 2-oxocyclopentanecarboxylic acid system.Key words: flash photolysis, photo-Wolff reaction, ketene hydration, enolization, ketonization, ketoenol equilibria, β-oxocarboxylic acids.
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 | 0.000 | 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 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".