Bibliographic record
Abstract
[124897-71-8] C7H15GeI (MW 298.71) InChI = 1S/C7H15GeI/c1-7(5-6-9)8(2,3)4/h1,5-6H2,2-4H3 InChIKey = RKYZZGGYYKBQRG-UHFFFAOYSA-N (precursor of lithium (3-trimethylgermyl-3-butenyl)cyanocuprate, a synthetically useful reagent for effecting annulation reactions1-3) Alternate Name: 3-iodo-1-methylenepropyltrimethylgermane. Physical Data: colorless liquid; distillation temperature (bulb-to-bulb) 85–92 °C/15 mmHg. Solubility: sol THF, CHCl3. Preparative Method: from 4-chloro-2-lithio-1-butene 1 (see 4‐Chloro‐2‐trimethylstannyl‐1‐butene) and from 1-trimethylsilyl-4-trimethylsilyloxy-1-butyne 3, as shown in eqs 1 and 2, respectively.1, 5 Of these two methods, the latter is experimentally more convenient and is also less expensive. (1) (2) Handling, Storage, and Precautions: organogermanium compounds4 and alkyl iodides are toxic and, therefore, the reagent should be prepared, distilled, and used in a fume hood. When stored in a freezer over copper wire under an inert atmosphere, the reagent is stable indefinitely. Should be distilled just prior to use; reactions should be carried out using dry THF and an inert atmosphere.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.022 |
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".