Evidence map›Paper›PMID 33103976›Full record

ArticleThe American journal of bioethics : AJOB2020

Structural Disparities in Data Science: A Prolegomenon for the Future of Machine Learning.

Niranjan S Karnik, Majid Afshar, Matthew M Churpek, Marcella Nunez-Smith

Abstract readComment
In one paragraph

Article in The American journal of bioethics : AJOB, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Summarizing Patients' Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models.Proceedings of COLING. International Conference on Computational Linguistics · 2022
    Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Niranjan S KarnikRush University.
Majid AfsharUniversity of Wisconsin.
Matthew M ChurpekUniversity of Wisconsin.
Marcella Nunez-SmithYale University.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
The Institute for Translational MedicineUL1TR002389 · NCATS · UNIVERSITY OF CHICAGO · PI Joshua J Jacobs, DAVID O MELTZER · 2017 to 2026
$71.6M
Yale Transdisciplinary Collaborative Center for Health Disparities Research (YALE-TCC)U54MD010711 · NIMHD · YALE UNIVERSITY · PI NUNEZ-SMITH, MARCELLA · 2016 to 2021
$14.4M
Quantifying How Cocaine Users Respond to Fentanyl Contamination in CocaineUG1DA049467 · NIDA · UNIVERSITY OF ILLINOIS AT CHICAGO · PI Niranjan Subhash Karnik, ANTONIO A MORGAN-LOPEZ · 2019 to 2026
$11.2M
Institutional Career Development Core (Chapter 1)KL2TR002387 · NCATS · UNIVERSITY OF CHICAGO · PI ERIC C BEYER, Lisa L Barnes · 2017 to 2026
$7.6M
Employing eSBI in a Community-based HIV Testing Environment for At-risk YouthR01DA041071 · NIDA · LURIE CHILDREN'S HOSPITAL OF CHICAGO · PI GAROFALO, ROBERT, KARNIK, NIRANJAN SUBHASH · 2015 to 2019
$3.2M
Sepsis Early Prediction and Subphenotype Illumination Study (SEPSIS)R01GM123193 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI CHURPEK, MATTHEW MICHAEL · 2017 to 2021
$1.9M
CHANGE OF GRANTEE INSTITUTION 1 K23 AA024503 Alcohol, Burn-Injury, and Acute Respiratory Distress SyndromeK23AA024503 · NIAAA · UNIVERSITY OF WISCONSIN-MADISON · PI AFSHAR, MAJID · 2016 to 2020
$948k
NCATS NIH HHS KL2 TR002387NCATS NIH HHS UL1 TR001863NCATS NIH HHS UL1 TR002389NIAAA NIH HHS K23 AA024503NIDA NIH HHS R01 DA041071NIDA NIH HHS UG1 DA049467NIGMS NIH HHS R01 GM123193NIMHD NIH HHS U54 MD010711
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Data ScienceMachine LearningForecastingHumansMorals

Identifiers

PMID33103976
PMCPMC7695219

What OpenQuestion holds

Textmetadata
LicenceTDM
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.