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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2022

Predicting occupational injury causal factors using text-based analytics: A systematic review

The record

Type
Publication
Date
15 September 2022
Level
International — held abroad
Journal
Frontiers in Public Health
Volume
10
Published
15 September 2022
DOI
10.3389/fpubh.2022.984099
Scopus ID
85139093837
ISSN
22962565
Authors
10
Open access
Yes
Citations
28
International co-authorship
Yes
Co-author countries
CN, IN, MY, TR

Classification

Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.

UN Sustainable Development Goals

  1. 8 Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all

    GoalPrimaryHigh confidenceJudged

    Text-based analytics and machine learning predict occupational injury causal factors to prevent workplace accidents and protect worker safety

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

  2. 9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending

    TargetSecondaryModerate confidenceJudged

    Development of NLP and deep learning methods for injury pattern extraction represents research capacity advancement

    Moderate confidence
    The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

  3. 17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing

    TargetSecondaryHigh confidenceRule-derivedrule sdg17-structural-v1

    Structural signal: co-authorship outside India.

    Rule-derived
    Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
    Produced by
    sdg17-structural-v1, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-4.4 Public safety, cybersecurity and national security

    Sub-themePrimaryHigh confidenceJudged

    Occupational injury prediction systems enhance workplace safety and accident prevention through data-driven insights

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

Each label above carries the instrument and the version that produced it. How each classification is reached.

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1

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Citing this record

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KIIT Deemed to be University. “Predicting occupational injury causal factors using text-based analytics: A systematic review”. Kortex.

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