Evidence map›Paper›PMID 30902894›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Automated, predictive, and interpretable inference of

Bryan C Daniels, William S Ryu, Ilya Nemenman

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Physics-tailored machine learning reveals unexpected physics in dusty plasmas.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  2. Article
  3. A dynamical model ofProceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Making Sense of Computational Psychiatry.The international journal of neuropsychopharmacology · 2020
    Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Bryan C DanielsArizona State University-Santa Fe Institute Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ 85281.ORCID 0000-0002-5870-1059
William S RyuDepartment of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada.
Ilya NemenmanDepartment of Physics, Emory University, Atlanta, GA 30322; ilya.nemenman@emory.edu.ORCID 0000-0003-3024-4244

Funding

Vocal motor control and sensorimotor learning - behavior, muscles, and neuronsR01NS084844 · NINDS · EMORY UNIVERSITY · PI SOBER, SAMUEL · 2013 to 2023
$3.8M
Neural mechanisms and behavioral consequences of non-Gaussian likelihoods in sensorimotor learningR01EB022872 · NIBIB · EMORY UNIVERSITY · PI NEMENMAN, ILYA M., SOBER, SAMUEL · 2016 to 2018
$1.2M
NIBIB NIH HHS R01 EB022872NINDS NIH HHS R01 NS084844
6 · The paper itself

Abstract

The roundworm

Indexed as

Hot TemperatureModels, BiologicalAnimalsCaenorhabditis elegansEscape Reactiondynamical systemsmachine learningnociceptionphenomenological models

Identifiers

PMID30902894
PMCPMC6462057

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.