Bibliographic record
Abstract
Abstract Selenium and tellurium form binary halides in which the chalcogen can be in formal oxidation states (IV), (II) or (I). They are versatile reagents for the preparation of a wide range of inorganic and organic selenium and tellurium compounds taking advantage of the reactivity of the chalcogen–halogen bond. With the exception of the tetrafluorides, the tetrahalides are either commercially available or readily prepared. On the other hand, the low-valent species, EX 2 (E = Se, Te; X = Cl, Br) and E 2 X 2 (E = Se, Te; X = Cl, Br) are unstable with respect to disproportionation and must be used as in situ reagents. Organoselenium and tellurium halides are well-known in oxidation states (IV) and (II), as exemplified by REX 3 , R 2 EX 2 and REX (R = alkyl, aryl; E = Se, Te; X = F, Cl, Br, I); mixed-valent (IV/II) compounds of the type RTeX 2 TeR are also known. This chapter surveys the availability and/or preparative methods for these widely used reagents followed by examples of their applications in synthetic inorganic and organic selenium and tellurium chemistry. For both the binary halides and their organic derivatives, the discussion is subdivided according to the formal oxidation state of the chalcogen.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| 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 | 0.002 |
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; both teacher heads agree on what is shown here.
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".