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Record W2967465153 · doi:10.1039/c9ob01645g

<i>Z</i>-isomerization of retinoids through combination of monochromatic photoisomerization and metal catalysis

2019· article· en· W2967465153 on OpenAlexfundno aff
Shirin Kahremany, Christopher L. Sander, Gregory P. Tochtrop, Adam Kubas, Krzysztof Palczewski

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2019
Typearticle
Languageen
FieldMaterials Science
TopicPhotochromic and Fluorescence Chemistry
Canadian institutionsnot available
FundersMinisterstwo Edukacji i NaukiNational Eye InstituteAllerganNational Institutes of HealthAlcon Research InstituteCanadian Institute for Advanced Research
KeywordsPhotoisomerizationMonochromatic colorIsomerizationPhotochemistryBlue lightCatalysisMetalChemistryMaterials scienceOpticsPhysicsOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

Catalytic Z-isomerization of retinoids to their thermodynamically less stable Z-isomer remains a challenge. In this report, we present a photochemical approach for the catalytic Z-isomerization of retinoids using monochromatic wavelength UV irradiation treatment. We have developed a straightforward approach for the synthesis of Z-retinoids in high yield, overcoming common obstacles normally associated with their synthesis. Calculations based on density functional theory (DFT) have allowed us to correlate the experimentally observed Z-isomer distribution of retinoids with the energies of chemically important intermediates, which include ground- and excited-state potential energy surfaces. We also demonstrate the application of the current method by synthesizing gram-scale quantities of 9-cis-retinyl acetate 9Z-a. Operational simplicity and gram-scale ability make this chemistry a very practical solution to the problem of Z-isomer retinoid synthesis.

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 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 score0.016
Threshold uncertainty score0.966

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)0.0010.000

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 head0.003
GPT teacher head0.194
Teacher spread0.190 · 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 teacher head, 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

Citations13
Published2019
Admission routes1
Has abstractyes

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