MétaCan
Menu
Back to cohort
Record W2320480613 · doi:10.1021/jp410586f

Modeling of Various Optical Spectra in the Presence of Slow Excitation Energy Transfer in Dimers and Trimers with Weak Interpigment Coupling: FMO as an Example

2014· article· en· W2320480613 on OpenAlexaff
Nicoleta Herascu, Adam Kell, Khem Acharya, Ryszard Jankowiak, Robert E. Blankenship, Valter Zazubovich

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsTrimerExcitationSpectral lineChemistryMolecular physicsCoupling (piping)Atomic physicsEmission spectrumAbsorption spectroscopyChemical physicsAbsorption (acoustics)Energy transferMonomerPhysicsDimerMaterials scienceOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

We present an improved simulation methodology to describe nonphotochemical hole-burned (NPHB) spectra. The model, which includes both frequency-dependent excitation energy transfer (EET) rate distributions and burning following EET, provides reasonable fits of various optical spectra including resonant and nonresonant holes in the case of FMO complex. A qualitative description of the NPHB process in light of a very complex protein energy landscape is briefly discussed. As an example, we show that both resonant and nonresonant HB spectra obtained for the 825 nm band of the trimeric FMO of C. tepidum are consistent with the presence of a relatively slow EET between the lowest energy states of the monomers of the trimer (mostly localized on BChl a 3), with a weak (∼1 cm(-1)) coupling between these states revealed via calculated emission spectra. We argue that the nature of the so-called 825 nm absorption band of the FMO trimer, contrary to the presently accepted consensus, cannot be explained by a single transition.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.245
Teacher spread0.232 · 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
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

Citations15
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry BSame topicSpectroscopy and Quantum Chemical StudiesFrench-language works237,207