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Record W2508770446 · doi:10.1021/acscombsci.6b00050

Efficient Routes to a Diverse Array of Amino Alcohol-Derived Chiral Fragments

2016· article· en· W2508770446 on OpenAlexfundno aff
Sina Haftchenary, Shawn D. Nelson, Laura Furst, Sivaraman Dandapani, Steven Ferrara, Žarko Bošković, Samuel Figueroa Lazú, Adrian M. Guerrero, Juan Carlos Serrano, DeMarcus K. Crews, Cristina Brackeen, Jeffrey Mowat, Thomas Brumby, Marcus Bauser, Stuart L. Schreiber, Andrew J. Phillips

Bibliographic record

VenueACS Combinatorial Science · 2016
Typearticle
Languageen
FieldChemistry
TopicOrganic and Inorganic Chemical Reactions
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesHarvard UniversityNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaBayerHoward Hughes Medical Institute
KeywordsChemistryAlcoholCombinatorial chemistryStereochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Efficient syntheses of chiral fragments derived from chiral amino alcohols are described. Several unique scaffolds were readily accessed in 1-5 synthetic steps leading to 45 chiral fragments, including oxazolidinones, morpholinones, lactams, and sultams. These fragments have molecular weights ranging from 100 to 255 Da and are soluble in water (0.085 to >15 mM).

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)0.000
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.249
Teacher spread0.236 · 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

Citations25
Published2016
Admission routes1
Has abstractyes

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