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Record W1521426154 · doi:10.1201/9780203492475

Assigning Structures to Ions in Mass Spectrometry

2006· book· en· W1521426154 on OpenAlexaff
Christiane Aubry, P. Mayer

Bibliographic record

Venuenot available
Typebook
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMass spectrometryIonChemistryComputer scienceChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Assigning Structures to Ions in Mass Spectrometry describes the tools currently available for determining gas-phase ion structures. It surveys current experimental methods for ion production and separation as well as those designed to reveal qualitative and quantitative aspects of gas-phase ions. It also examines how and when to apply computational chemistry and theoretical calculations. Selected case studies illustrate specific challenges associated with ion structure assignment and thermochemical problems. Bringing together key results collected over the past four decades, the book contains the data for describing or identifying ions containing C alone and C with H, O, N, S, P, halogens, and small organic cations.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0180.018

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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations84
Published2006
Admission routes1
Has abstractyes

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