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Record W1992252019 · doi:10.1002/mas.20225

The mechanisms of collisional activation of ions in mass spectrometry

2009· article· en· W1992252019 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMass Spectrometry Reviews · 2009
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryProjectileIonAtomic physicsExcitationCollisionMass spectrometryTranslational energyCollisional excitationIonizationPhysics

Abstract

fetched live from OpenAlex

This article is a review of the mechanisms responsible for collisional activation of ions in mass spectrometers. Part I gives a general introduction to the processes occurring when a projectile ion and neutral target collide. The theoretical background to the physical phenomena of curve-crossing excitation (for electronic and vibrational excitation), impulsive collisions (for direct translational to vibrational energy transfer), and the formation of long-lived collision intermediates is presented. Part II highlights the experimental and computational investigations that have been made into collisional activation for four experimental conditions: high (>100 eV) and intermediate (1-100 eV) center-of-mass collision energies, slow heating collisions (multiple low-energy collisions) and collisions with surfaces. The emphasis in this section is on the derived post-collision internal energy distributions that have been found to be typical for projectile ions undergoing collisions in these regimes.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.020
GPT teacher head0.287
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it