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Record W2011047245 · doi:10.1021/ci900350h

2D Depiction of Fragment Hierarchies

2009· article· en· W2011047245 on OpenAlexaff
Alex M. Clark

Bibliographic record

VenueJournal of Chemical Information and Modeling · 2009
Typearticle
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsDepictionFragment (logic)Tree (set theory)Computer scienceOrientation (vector space)SubstructureTree structureStructural motifData structureAlgorithmChemistryCombinatoricsMathematicsGeometryProgramming languageArtEngineering

Abstract

fetched live from OpenAlex

Drug discovery projects often involve organizing compounds in the form of a hierarchical tree, where each node is a substructure fragment shared by all of its descendent nodes. A method is described for producing 2D depiction layout coordinates for each of the nodes in such a tree, ensuring that common fragments within molecular structures are drawn in an identical way, and arranged with a consistent orientation. This is achieved by first deriving a common numbering scheme for common fragments, then using this scheme to redepict each of the molecules, one fragment at a time, so that common fragments have common depiction motifs. Once complete, the distinct root branches can be overlaid onto each other, after which all of the fragments and whole molecules have a common layout and orientation. Several methods are described for preparing visual representations of molecular structure hierarchies alongside activity information. Combining high level tree display and structure depiction showing common features readily facilitates insight into structure-activity relationships.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.478
Threshold uncertainty score0.146

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 communication0.0000.002
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 head0.024
GPT teacher head0.295
Teacher spread0.271 · 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 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

Citations18
Published2009
Admission routes1
Has abstractyes

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