Bibliographic record
Abstract
The intrinsic chemical reactivities of ions can be monitored in the gas phase using mass spectrometers that are coupled to appropriate ion sources and reaction cells. Here the author surveys his own experiences over the past 40 years as an ion chemist. He used flow-tube techniques for room temperature measurements of the intrinsic chemical reactivities of a large variety of positive and negative ions, including bare atomic ions, ions found in solution, biological ions, carbonaceous ions, and interstellar, cometary, and ionospheric ions. Progress in the measurement of chemical reactions of these ions with flow-tube mass spectrometry in the author’s laboratory was been driven largely by developments in techniques of ion injection into the flow tube and of ion production (e.g., by electron impact, plasma ionization, and electrospray ionization). Chemical topics that are covered include: acid-base and nucleophilic displacement reactions that have bridged the gap between the gas phase and solution; interstellar ions and their role in molecular synthesis such as the synthesis of amino acids; the chemistry of fullerene cations as a function of charge state; fundamentals and applications of the chemistry of atomic cations with an emphasis on transition metal and lanthanide cations; atomic metal-ion catalysis; and chemical reactions of singly and multiply charged biological anions and cations in the gas phase.Key words: ions, mass spectrometry, kinetics, ion chemistry.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".