DOI: 10.2337/db06-1595 link

PMID: 17519423

OpenAlex ID: W2137274603

Category: Biomedical

Title: Loss-of-Function Mutation in Toll-Like Receptor 4 Prevents Diet-Induced Obesity and Insulin Resistance

Authors: Daniela Miti Lemos Tsukumo, Rui Curi, Lı́cio A. Velloso, Mário José Abdalla Saad, Marco Antônio de Carvalho-Filho, José B.C. Carvalheira, ... (11 authors, truncated)

Publishing Date: 01-Aug-2007

YCR = 2007  / 738 /  13.25 

Version 1.00            Year       /   Citations  /   Relative

Metric Value Date of Calculation

Citations count

738

30-May-2024

Relative

13.25

04-Aug-2024

Same Authors in Other Papers:

Logic 1 Same First Author: A first author detected by OpenAlex algorithm with possibility of multiple first authors. Good R-values of the same first author(s) as a first author(s) in other papers: no data (not found)

Logic 2 Same Authors in Any Team: Good R-values of the same authors with any team in other papers: 30.51, 28.54, 27.15, 17.83, 17.31, 16.30, 15.64, 13.58, 12.28, 12.02, 11.87, 11.66, 10.67, 9.73, 9.50, ... (470 found, truncated)

Same Authors Duplicates: duplicates across 2 logical groups are not added up in the final calculation, duplicates are shown with asterisk*.

Same Authors Total Good R-values: same authors total good non-duplicated R-values for above 2 logical groups: 470

Article Expected CPY (Citations per Year): 3.28 Expected CPY Help

Article Actual CPY: 43.41 Actual CPY Help

Article Co-Citation FCR (Field Citation Rate): 5.34 FCR Help

Article Co-Citation Network Size: 71206 Co-Citation Network Size Help

Article Topics: Inflammation and Obesity-Related Metabolic Disorders, Innate Immune Recognition and Signaling Pathways, Natural Killer Cells in Immunity Topics help

Article Keywords: Toll-like Receptors, Insulin Resistance, Adaptive Immunity Regulation, Type 2 Diabetes, NOD-Like Receptors Keywords Help

Journal: Diabetes

Journal IF-ycr: 8.292 Journal IF-ycr Help

Journal short code: NA

Journal ISSN: 0012-1797

Journal OA-ID: 129060628

Help

Expected CPY Help: Predicted citations per year for this article, derived from its Field Citation Rate (FCR) using a benchmark regression of NIH-funded papers. Values above actual CPY indicate under-performance; below indicate over-performance. Used as the denominator of the Relative Citation Ratio.

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Actual CPY Help: Average yearly citations the article has received from publication through the current year, adjusted for partial years. Used as the numerator of the Relative Citation Ratio.

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FCR Help: Mean journal citation rate for all papers in the article's co-citation network. For each network paper we substitute its journal’s impact factor (calculated from open data) as a proxy for citations per year, then average these values. This captures the citation intensity of the article's immediate research field and forms the basis for computing expected CPY.

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Co-Citation Network Size Help: Number of unique papers co-cited with this article by its citing papers; larger networks yield more stable field estimates when calculating FCR and expected CPY.

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Topics Help: OpenAlex assigns topics to each paper with an AI model that considers the title, abstract, journal, and citation links. Tags are chosen from about 4,500 research areas, and the highest-confidence tag becomes the paper's primary topic. Every topic sits in a hierarchy of domain, field, and subfield, so you can see exactly where the work fits in the wider map of science.

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Keywords Help: Keywords are generated automatically from the paper's assigned topics. The OpenAlex system selects candidate terms, then keeps up to five that match closely with the title or abstract. These keywords highlight specific concepts or methods and give a quick complement to the broader topic tags.

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Journal IF-ycr Help: Journal IF-ycr is a two-year impact factor recalculated from OpenAlex's open citation data. For a given journal and year Y, we:

  1. Count citations made in year Y by any paper to items that the journal published in years Y-1 and Y-2 (excluding the current year).
  2. Divide that citation count by the number of articles the journal published in those same two years.
This yields an impact factor analogue built entirely from open data, updated annually and used in the YCR workflow.

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