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Record W7008634644

Computing Rovibrational Spectra of Small Polyatomic Molecules with Variational and Collocation Methods

2019· dissertation· en· W7008634644 on OpenAlexaff

Bibliographic record

VenueQSpace (Queen's University Library) · 2019
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsProteogenomicsNucleofectionArticular cartilage damageGulagDiafiltrationFusible alloy
DOInot available

Abstract

fetched live from OpenAlex

It is well-known that some deuterated isotopologues of interstellar molecules achieve a significantly higher deuterium-to-hydrogen ratio than the natural elemental abundance. CH3+ and its deuterated isotopologues are thought to be an important mediator of this process in warm interstellar regions and as such their detection is of interest. To assist in experimental observation, rovibrational calculations have been performed for all isotopologues of CH3+ up to J = 5. Rovibrational levels of CH2D+ and CD2H+ are computed for the first time. Vibrational states up to the 5000-6000 cm-1 range are assigned and their symmetry is determined. The J < 6 levels for the ground, ν1, and ν5 states of CH2D+, and the ground state of CD2H+ compared to observed levels all have a root-mean-square-error (rmse) of less than 0.1 cm-1. The rmse increases to over 0.5 cm-1 for the ν1 mode of CD2H+, thought to be due to a perturbation with another band. Though prior analysis proposes the ν2 +ν 3 overtone as most likely for a perturbing Fermi resonance, these calculations suggest 3ν 3 as the more probable candidate. In addition, the progress on an additional project aimed at supplementing sum-of- products routines is outlined. Preliminary results for P2O look promising, and calculations are presently moving forward on a CH2O example to test the proposed idea.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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 designSimulation or modeling
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

Citations0
Published2019
Admission routes1
Has abstractyes

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