MétaCan
Menu
Back to cohort
Record W2052995674 · doi:10.1063/1.1428752

A preconditioned inexact spectral transform method for calculating resonance energies and widths, as applied to HCO

2002· article· en· W2052995674 on OpenAlex
Bill Poirier, Tucker Carrington

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.

Bibliographic record

VenueThe Journal of Chemical Physics · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsLanczos resamplingPreconditionerSolverHamiltonian (control theory)Iterative methodApplied mathematicsMathematicsEigenvalues and eigenvectorsLanczos algorithmPhysicsAlgorithmMathematical optimizationQuantum mechanics

Abstract

fetched live from OpenAlex

We present a complex-symmetric version of the preconditioned inexact spectral transform (PIST) method, for calculating resonance energies and widths. The PIST method uses an iterative linear solver to compute inexact Lanczos vectors for (EI−H)−1, and then diagonalizes the Hamiltonian in the inexact Lanczos representation. Our new version requires complex-symmetric variants of: (1) the Lanczos algorithm, (2) the linear solver, (3) the preconditioner we introduced in a previous paper [J. Chem. Phys. 114, 9254 (2001)]. The new method works extremely well for HCO, enabling us to calculate the first 17 dissociative resonances in less then 90 second of CPU time.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.564

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)0.0000.000

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 head0.014
GPT teacher head0.275
Teacher spread0.261 · 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