DOI: 10.1007/s40745-022-0038
1-0 link

PMID: NA

OpenAlex ID: W4220667573

Category: Biomedical

Title: A Machine Learning Model for Predicting Individual Substance Abuse with Associated Risk-Factors

Authors: Uwaise Ibna Islam, Enamul Haque, Dheyaaldin Alsalman, Muhammad Nazrul Islam, Mohammad Ali Moni, Iqbal H. Sarker

Publishing Date: 23-Mar-2022

YCR = 2022  /   8   /  2.97 

Version 1.00            Year       /   Citations  /   Relative

Metric Value Date of Calculation

Citations count

8

30-May-2024

Relative

2.97

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: 286, 269, 95.70, 93.33, 66.10, 48.84, 44.52, 31.23, 26.06, 23.61, 21.19, 20.17, 15.92, 14.81, 13.33, ... (172 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: 172

Article Expected CPY (Citations per Year): 1.35 Expected CPY Help

Article Actual CPY: 4.00 Actual CPY Help

Article Co-Citation FCR (Field Citation Rate): 2.20 FCR Help

Article Co-Citation Network Size: 294 Co-Citation Network Size Help

Article Topics: Epidemiology and Interventions for Substance Use Disorders, Pathogenesis and Treatment of Alcoholic Liver Disease, Global Epidemiology of HIV and Drug Use Topics help

Article Keywords: Substance Abuse, drug use, Alcohol Dependence, risk environment, Substance Use Disorders Keywords Help

Journal: Annals of data science

Journal IF-ycr: 3.200 Journal IF-ycr Help

Journal short code: NA

Journal ISSN: 2198-5804

Journal OA-ID: 2765063436

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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