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Record W2164951764 · doi:10.1139/v08-184

Comparing the fragmentation chemistry of gas-phase adducts of poly(dimethylsiloxane) oligomers with metal and organic ions

2009· article· en· W2164951764 on OpenAlexafffundvenue
Justin B. Renaud, Abdulhrahman M. Alhazmi, P. Mayer

Bibliographic record

VenueCanadian Journal of Chemistry · 2009
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Ottawa
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaUniversities Space Research Association
KeywordsChemistryAdductProtonationOligomerSiloxaneFragmentation (computing)Electrospray ionizationMetal ions in aqueous solutionIonPolymer chemistryMass spectrometryPhotochemistryOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Gas-phase ions of poly(dimethylsiloxane) oligomers were formed by electrospray ionization either by protonating them in solution with formic acid or by generating adducts of the oligomers with the metal ions Li + , Na + , K + , and Ag + as well as with the organic cations NH 4 + , CH 3 CH 2 NH 3 + , and protonated glycine, aspartic acid, and 1,2-diphenylethylamine. The collision-induced fragmentation of the oligomeric ions was strongly dependent on the nature of the charging species. Ag + adducts dissociated in a manner previously observed in secondary ion mass spectrometry experiments generating a series of linear and cyclic fragment ions, while Li + adducts fragmented to form two ions: an adduct of the metal ion with the oligomer end-group and one with the remaining oligomer. Na + and K + adducts simply dissociate to form the bare metal ion. The organic species, to varying extents, transfer the proton to the oligomer to form a protonated poly(siloxane) ion. These protonated oligomers then dissociate at very low laboratory-frame collision energy along the siloxane backbone by loss of a silanol. These backbone fragments can then lose a methyl group to form a second series of fragment ions. Suggestions for probable mechanistic pathways for these processes are presented.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.239
Teacher spread0.229 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2009
Admission routes3
Has abstractyes

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