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Record W3035270113 · doi:10.1039/d0ra04028b

A novel artificial intelligence protocol to investigate potential leads for Parkinson's disease

2020· article· en· W3035270113 on OpenAlexaff
Zhidong Chen, Lu Zhao, Hsin‐Yi Chen, Jia-Ning Gong, Xu Chen, Calvin Yu‐Chian Chen

Bibliographic record

VenueRSC Advances · 2020
Typearticle
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersJunta de Castilla y LeónScience, Technology and Innovation Commission of Shenzhen MunicipalitySun Yat-sen University
KeywordsIndole testDocking (animal)Traditional Chinese medicineComputational biologyQuantitative structure–activity relationshipChemistryCombinatorial chemistryPharmacologyBioinformaticsMedicineStereochemistryBiologyPathology

Abstract

fetched live from OpenAlex

). The results showed that 2007_22057 (an indole derivative), 2007_22325 (a valine anhydride) and 2007_15317 (an indole derivative) might be a potential medicine formula for the treatment of PD. Then there are three candidate compounds identified by the result of molecular dynamics.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.297
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.071
GPT teacher head0.361
Teacher spread0.290 · 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
GenreMethods

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

Citations19
Published2020
Admission routes1
Has abstractyes

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