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Record W2000231090 · doi:10.1139/v04-114

New method of energymass dispersion applied to mass spectral data from positively charged water vapor clusters

2004· article· en· W2000231090 on OpenAlexvenueno aff
G. E. Walrafen, Hugh R. Carlon

Bibliographic record

VenueCanadian Journal of Chemistry · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryMass spectrumBar (unit)Water vaporEnthalpyDispersion (optics)Analytical Chemistry (journal)Mass spectrometryVapor pressureCondensationThermodynamicsChromatographyPhysicsOpticsMeteorology

Abstract

fetched live from OpenAlex

A new method is presented by which energy–mass, volume–mass, and enthalpy–mass dispersion curves may be determined for charged water vapor clusters. This method involves two closely spaced partial pressures at a fixed temperature. The method is exemplified by using mass spectral data from positively charged water vapor clusters (H+(H2O)M) where 6 ≤ M ≤ 45. A ΔG–mass dispersion was also determined using the ΔH–mass dispersion for comparison. ΔG displays an enormous minimum, which is of signal importance because it indicates that a size of maximum stability (SMS) exists. The SMS corresponds to M = 13 for pressures between 0.056 and 0.151 bar (1 bar = 100 kPa) at 373.15 K, and to M = 32±1 for pressures between 0.473 and 0.556 bar at 372.15 K. The free energy corresponding to M = 45 occurs far above that corresponding to the SMS. The resultant instability leads to condensation for pressures above 0.556 bar at 372.15 K.Key words: clusters, mass spectrometry, thermodynamics, water vapour.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.005
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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 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

Citations1
Published2004
Admission routes1
Has abstractyes

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