On the public citation graph

AutoML for Multi-Label Classification: Overview and Empirical Evaluation

https://doi.org/10.1109/tpami.2021.3051276

0 signed · 147 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/3-540-07165-2_55openalex-snapshot

On bayesian methods for seeking the extremum

inferredcites →https://doi.org/10.1007/978-0-387-09823-4_34openalex-snapshot

Mining Multi-label Data

inferredcites →https://doi.org/10.1007/978-3-030-05318-5openalex-snapshot

Automated Machine Learning

inferredcites →https://doi.org/10.1007/978-3-030-05318-5_4openalex-snapshot

Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKA

inferredcites →https://doi.org/10.1007/978-3-030-05318-5_5openalex-snapshot

Hyperopt-Sklearn

inferredcites →https://doi.org/10.1007/978-3-030-34885-4_1openalex-snapshot

CascadeML: An Automatic Neural Network Architecture Evolution and Training Algorithm for Multi-label Classification (Best Technical Paper)

inferredcites →https://doi.org/10.1007/978-3-030-43823-4_7openalex-snapshot

ReinBo: Machine Learning Pipeline Conditional Hierarchy Search and Configuration with Bayesian Optimization Embedded Reinforcement Learning

inferredcites →https://doi.org/10.1007/978-3-030-44584-3_44openalex-snapshot

LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-label Classification

inferredcites →https://doi.org/10.1007/978-3-030-61527-7_21openalex-snapshot

Extreme Algorithm Selection with Dyadic Feature Representation

inferredcites →https://doi.org/10.1007/978-3-319-01595-8_18openalex-snapshot

On the Problem of Error Propagation in Classifier Chains for Multi-label Classification

inferredcites →https://doi.org/10.1007/978-3-319-55696-3_16openalex-snapshot

RECIPE: A Grammar-Based Framework for Automatically Evolving Classification Pipelines

inferredcites →https://doi.org/10.1007/978-3-319-99259-4_25openalex-snapshot

Automated Selection and Configuration of Multi-Label Classification Algorithms with Grammar-Based Genetic Programming

inferredcites →https://doi.org/10.1007/978-3-540-74958-5_61openalex-snapshot

Ensembles of Multi-Objective Decision Trees

inferredcites →https://doi.org/10.1007/978-3-642-25566-3_40openalex-snapshot

Sequential Model-Based Optimization for General Algorithm Configuration

inferredcites →https://doi.org/10.1007/978-3-662-38527-2_55openalex-snapshot

On Bayesian Methods for Seeking the Extremum

inferredcites →https://doi.org/10.1007/s10618-018-0595-5openalex-snapshot

Multi-target prediction: a unifying view on problems and methods

inferredcites →https://doi.org/10.1007/s10710-010-9109-yopenalex-snapshot

Grammar-based Genetic Programming: a survey

inferredcites →https://doi.org/10.1007/s10994-011-5256-5openalex-snapshot

Classifier chains for multi-label classification

inferredcites →https://doi.org/10.1007/s10994-018-5735-zopenalex-snapshot

ML-Plan: Automated machine learning via hierarchical planning

inferredcites →https://doi.org/10.1007/s10994-020-05879-3openalex-snapshot

An empirical analysis of binary transformation strategies and base algorithms for multi-label learning

inferredcites →https://doi.org/10.1007/s11704-017-7031-7openalex-snapshot

Binary relevance for multi-label learning: an overview

inferredcites →https://doi.org/10.1016/j.knosys.2020.106622openalex-snapshot

AutoML: A survey of the state-of-the-art

inferredcites →https://doi.org/10.1023/a:1008306431147openalex-snapshot

Efficient Global Optimization of Expensive Black-Box Functions

inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1108/ir.2005.04932eae.001openalex-snapshot

Automated Planning: Theory and Practice

inferredcites →https://doi.org/10.1109/bracis.2018.00029openalex-snapshot

Bandit-Based Automated Machine Learning

inferredcites →https://doi.org/10.1109/scc.2018.00039openalex-snapshot

(WIP) Towards the Automated Composition of Machine Learning Services

inferredcites →https://doi.org/10.1109/tkde.2013.39openalex-snapshot

A Review on Multi-Label Learning Algorithms

inferredcites →https://doi.org/10.1137/070693424openalex-snapshot

A Knowledge-Gradient Policy for Sequential Information Collection

inferredcites →https://doi.org/10.1145/2487575.2487629openalex-snapshot

Auto-WEKA

inferredcites →https://doi.org/10.1145/2908812.2908918openalex-snapshot

Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science

inferredcites →https://doi.org/10.1145/3067695.3082053openalex-snapshot

Towards a method for automatically selecting and configuring multi-label classification algorithms

inferredcites →https://doi.org/10.1145/3205455.3205586openalex-snapshot

Autostacker

inferredcites →https://doi.org/10.1613/jair.1.11854openalex-snapshot

Benchmark and Survey of Automated Machine Learning Frameworks

inferredcites →https://doi.org/10.21105/joss.01132openalex-snapshot

GAMA: Genetic Automated Machine learning Assistant

inferredcites →https://doi.org/10.24963/ijcai.2019/457openalex-snapshot

Automated Machine Learning with Monte-Carlo Tree Search

inferredcites →https://doi.org/10.4018/jdwm.2007070101openalex-snapshot

Multi-Label Classification

inferredcites →https://doi.org/10.48550/arxiv.1206.2944openalex-snapshot

Practical Bayesian Optimization of Machine Learning Algorithms

inferredcites →https://doi.org/10.48550/arxiv.1502.07943openalex-snapshot

Non-stochastic Best Arm Identification and Hyperparameter Optimization

inferredcites →https://doi.org/10.48550/arxiv.1603.06560openalex-snapshot

Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization

inferredcites →https://doi.org/10.48550/arxiv.1807.02811openalex-snapshot

A Tutorial on Bayesian Optimization

inferredcites →https://doi.org/10.48550/arxiv.1808.06492openalex-snapshot

Benchmarking Automatic Machine Learning Frameworks

inferredcites →https://doi.org/10.48550/arxiv.1809.00486openalex-snapshot

Automated Machine Learning Service Composition

inferredcites →https://doi.org/10.48550/arxiv.1810.13306openalex-snapshot

Automated Machine Learning: From Principles to Practices

inferredcites →https://doi.org/10.48550/arxiv.1811.04060openalex-snapshot

Automated Multi-Label Classification based on ML-Plan

inferredcites →https://doi.org/10.48550/arxiv.1811.11353openalex-snapshot

Multi-label classification search space in the MEKA software

inferredcites →https://doi.org/10.48550/arxiv.1906.02287openalex-snapshot

Automated Machine Learning: State-of-The-Art and Open Challenges

inferredcites →https://doi.org/10.48550/arxiv.2003.06505openalex-snapshot

AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

inferredcites →https://doi.org/10.48550/arxiv.2111.02508openalex-snapshot

AlphaD3M: Machine Learning Pipeline Synthesis

inferredcites →https://doi.org/10.5167/uzh-67514openalex-snapshot

Designing KDD-Workflows via HTN-Planning for Intelligent Discovery Assistance

inferredcites →https://doi.org/10.5555/2188385.2343701openalex-snapshot

Entropy search for information-efficient global optimization

inferredcites →https://doi.org/10.57702/tmdwazw3openalex-snapshot

MEKA: A multi-label/multi-target extension to Weka

inferredcites →https://doi.org/10.7551/mitpress/3927.001.0001openalex-snapshot

An Introduction to Genetic Algorithms

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4350765openalex-extracted

Automated Threshold Learning for Feature Selection Optimization

inferred← citeshttps://doi.org/10.1002/9781394272426.ch1openalex-snapshot

Design and Architecture of AutoML for Data Science in Next‐Generation Industries

inferred← citeshttps://doi.org/10.1002/9781394272426.ch9openalex-snapshot

AutoML Ecosystem and Open‐Source Platforms

inferred← citeshttps://doi.org/10.1002/ail2.118openalex-snapshot

Improving Machine Learning Workflows Using the “Normative‐Descriptive‐Prescriptive” Decision Framework

inferred← citeshttps://doi.org/10.1002/smll.202311101openalex-snapshot

Hollow CoFe Nanozymes Integrated with Oncolytic Peptides Designed via Machine‐Learning for Tumor Therapy

inferred← citeshttps://doi.org/10.1007/978-3-031-12670-3_10openalex-snapshot

Multi-label Online Streaming Feature Selection Algorithms via Extending Alpha-Investing Strategy

inferred← citeshttps://doi.org/10.1007/978-3-031-30047-9_31openalex-snapshot

Meta-learning for Automated Selection of Anomaly Detectors for Semi-supervised Datasets

inferred← citeshttps://doi.org/10.1007/978-3-031-45389-2_20openalex-snapshot

AutoMMLC: An Automated and Multi-objective Method for Multi-label Classification

inferred← citeshttps://doi.org/10.1007/978-3-031-75233-9_7openalex-snapshot

Hyperparameter Optimization of Multi-layer Perceptron-Based Predictors

inferred← citeshttps://doi.org/10.1007/978-3-031-75577-4_1openalex-snapshot

Location, Size, and Capacity

inferred← citeshttps://doi.org/10.1007/978-3-031-84062-3_25openalex-snapshot

Advancing the Machine Learning Workflow: A Comprehensive Analysis of Auto Machine Learning (Auto-ML) Techniques and Future Investigations

inferred← citeshttps://doi.org/10.1007/978-3-032-04403-7_26openalex-snapshot

AutoML: A Tertiary Study of Phases, Methods, Tools, and Frameworks

inferred← citeshttps://doi.org/10.1007/978-981-95-1565-3_35openalex-snapshot

A Multi Label Based Classification Method for Commodity Risk Assessment

inferred← citeshttps://doi.org/10.1007/978-981-95-4813-2_21openalex-snapshot

ML-Maestro: No Code Machine Learning with Interactive Data Visualization

inferred← citeshttps://doi.org/10.1007/978-981-97-1949-5_140openalex-snapshot

Automated Machine Learning in the Smart Construction Era: Significance and Accessibility for Industrial Classification and Regression Tasks

inferred← citeshttps://doi.org/10.1007/s00261-024-04685-yopenalex-snapshot

Radiomics-based automated machine learning for differentiating focal liver lesions on unenhanced computed tomography

inferred← citeshttps://doi.org/10.1007/s10462-023-10569-2openalex-snapshot

A systematic literature review on AutoML for multi-target learning tasks

inferred← citeshttps://doi.org/10.1007/s10462-025-11397-2openalex-snapshot

A literature review on automated machine learning

inferred← citeshttps://doi.org/10.1007/s10479-024-06434-2openalex-snapshot

Customer emotion detection and analytics in hotel and tourism services using multi-label classificational models based on ensemble learning

inferred← citeshttps://doi.org/10.1007/s10489-022-04350-1openalex-snapshot

Multi-label learning with Relief-based label-specific feature selection

inferred← citeshttps://doi.org/10.1007/s10489-023-04770-7openalex-snapshot

Automated machine learning with dynamic ensemble selection

inferred← citeshttps://doi.org/10.1007/s10994-022-06161-4openalex-snapshot

Algorithm selection on a meta level

inferred← citeshttps://doi.org/10.1007/s10994-025-06923-wopenalex-snapshot

Minimal learning machine for multi-label learning

inferred← citeshttps://doi.org/10.1007/s11053-026-10737-5openalex-snapshot

Automated Machine Learning Method for Complex Lithology Identification Using Deep Adaptive Stacking

inferred← citeshttps://doi.org/10.1007/s12553-025-01041-yopenalex-snapshot

Can reasoning LLMs enhance clinical document classification?

inferred← citeshttps://doi.org/10.1007/s13042-024-02349-3openalex-snapshot

Clustered Automated Machine Learning (CAML) model for clinical coding multi-label classification

inferred← citeshttps://doi.org/10.1016/j.asoc.2025.112740openalex-snapshot

Dynamic Q&A multi-label classification based on adaptive multi-scale feature extraction

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106467openalex-snapshot

TSSK-Net: Weakly supervised biomarker localization and segmentation with image-level annotation in retinal OCT images

inferred← citeshttps://doi.org/10.1016/j.engappai.2025.110934openalex-snapshot

Data-driven forecasting and its role in enhanced decision-making

inferred← citeshttps://doi.org/10.1016/j.engappai.2025.112035openalex-snapshot

Automated machine learning for residential property valuation

inferred← citeshttps://doi.org/10.1016/j.jiixd.2023.10.002openalex-snapshot

AutoML: A systematic review on automated machine learning with neural architecture search

inferred← citeshttps://doi.org/10.1016/j.nexres.2026.101913openalex-snapshot

AutoEns: An intelligent framework for automated ensemble learning model development and deployment

inferred← citeshttps://doi.org/10.1016/j.procs.2022.07.005openalex-snapshot

Automated Machine Learning based Elderly Fall Detection Classification

inferred← citeshttps://doi.org/10.1016/j.tplants.2023.09.008openalex-snapshot

AutoML: advanced tool for mining multivariate plant traits

inferred← citeshttps://doi.org/10.1021/envhealth.5c00623openalex-snapshot

AI-Enabled Mapping of Structure-Hazard Relationships for Emerging Contaminants

inferred← citeshttps://doi.org/10.1038/s41598-023-40904-0openalex-snapshot

Hierarchical automated machine learning (AutoML) for advanced unconventional reservoir characterization

inferred← citeshttps://doi.org/10.1038/s41598-025-02149-xopenalex-snapshot

A practical evaluation of AutoML tools for binary, multiclass, and multilabel classification

inferred← citeshttps://doi.org/10.1057/s41254-024-00324-xopenalex-snapshot

Terminology, AI bias, and the risks of current digital public diplomacy practices

inferred← citeshttps://doi.org/10.1063/5.0305667openalex-snapshot

Streamlined data profiling and automated machine learning model generation

inferred← citeshttps://doi.org/10.1109/access.2024.3430558openalex-snapshot

Multi-Label Code Error Classification Using CodeT5 and ML-KNN

inferred← citeshttps://doi.org/10.1109/access.2024.3525061openalex-snapshot

Source Code Error Understanding Using BERT for Multi-Label Classification

inferred← citeshttps://doi.org/10.1109/access.2026.3723560openalex-snapshot

MCTS-Plan: A History-Aware Adaptive Search Framework for Hierarchical AutoML in Multi-Label Classification

inferred← citeshttps://doi.org/10.1109/acit62805.2024.10877009openalex-snapshot

Multi Label Classification Algorithm Based on Conditional Local Correlations among Labels and Ensemble Learning

inferred← citeshttps://doi.org/10.1109/aeis61544.2023.00012openalex-snapshot

Feature Engineering Procedure for Information Enrichment

inferred← citeshttps://doi.org/10.1109/cec60901.2024.10611918openalex-snapshot

Evolutionary Label Selection for Multi-label Classification

inferred← citeshttps://doi.org/10.1109/edge60047.2023.00060openalex-snapshot

Towards Intelligent Data Protocols for the Edge

inferred← citeshttps://doi.org/10.1109/fuzz-ieee55066.2022.9882828openalex-snapshot

A Multi-label Approach for Diagnosis Problems in Energy Systems using LAMDA algorithm

inferred← citeshttps://doi.org/10.1109/iccds60734.2024.10560426openalex-snapshot

A Novel Approach to Protect Environment by CO 2 Emission Detection

inferred← citeshttps://doi.org/10.1109/icdcece65353.2025.11035198openalex-snapshot

Multi-Label Classification of English Social Media Texts based on Deep Learning Algorithm

inferred← citeshttps://doi.org/10.1109/icsa-c65153.2025.00076openalex-snapshot

POE-ML: An Automated Pipeline for Optimization and Evaluation of Machine Learning

inferred← citeshttps://doi.org/10.1109/icscss60660.2024.10625466openalex-snapshot

AutoML Based Tourism Prediction and Maximising Revenue

inferred← citeshttps://doi.org/10.1109/icstcee56972.2022.10100217openalex-snapshot

Automated ECG Arrhythmia classification using Resnet and AutoML Learning Model

inferred← citeshttps://doi.org/10.1109/ieeeconf56737.2023.10092157openalex-snapshot

Multi-Label Learning in Computer Networks

inferred← citeshttps://doi.org/10.1109/ijcnn55064.2022.9892282openalex-snapshot

Feature Pyramid Vision Transformer for MedMNIST Classification Decathlon

inferred← citeshttps://doi.org/10.1109/inocon57975.2023.10101357openalex-snapshot

Automating the Machine Learning Process using PyCaret and Streamlit

inferred← citeshttps://doi.org/10.1109/jiot.2025.3592954openalex-snapshot

Federated Learning on Multilabel Evolving Data Streams

inferred← citeshttps://doi.org/10.1109/sisimpact67725.2025.11439368openalex-snapshot

Evaluating AutoML Frameworks in the Context of Autism Diagnosis: A Comparative Analysis

inferred← citeshttps://doi.org/10.1109/tce.2026.3651524openalex-snapshot

Auto-EAD: An Automated Ensemble Anomaly Detection Framework for the CEN-IoT

inferred← citeshttps://doi.org/10.1109/tim.2025.3550221openalex-snapshot

Transformer OLTC Operation Monitoring Framework Through Acoustic Signal Processing and Convolutional Neural Networks

inferred← citeshttps://doi.org/10.1109/tmm.2026.3668556openalex-snapshot

Correlative Fusion-Based Multi-Instance Partial Multi-Label Learning

inferred← citeshttps://doi.org/10.1109/tnnls.2023.3238729openalex-snapshot

Automatic Metric Search for Few-Shot Learning

inferred← citeshttps://doi.org/10.1109/tnnls.2024.3369064openalex-snapshot

A Multitask Dynamic Graph Attention Autoencoder for Imbalanced Multilabel Time Series Classification

inferred← citeshttps://doi.org/10.1109/tpami.2021.3077106openalex-snapshot

Guest Editorial: Automated Machine Learning

inferred← citeshttps://doi.org/10.1109/tpami.2021.3126216openalex-snapshot

2021 Index IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 43

inferred← citeshttps://doi.org/10.1109/tpami.2022.3188547openalex-snapshot

Integrating Multi-Label Contrastive Learning With Dual Adversarial Graph Neural Networks for Cross-Modal Retrieval

inferred← citeshttps://doi.org/10.1117/12.2641065openalex-snapshot

Recognition for American Sign Language letters based on AutoML platform

inferred← citeshttps://doi.org/10.1145/3449639.3459395openalex-snapshot

Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance

inferred← citeshttps://doi.org/10.1145/3532190openalex-snapshot

Integrating Global and Local Feature Selection for Multi-Label Learning

inferred← citeshttps://doi.org/10.1145/3637528.3672015openalex-snapshot

Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning

inferred← citeshttps://doi.org/10.1145/3712256.3726330openalex-snapshot

SynthACticBench: A Capability-Based Synthetic Benchmark for Algorithm Configuration

inferred← citeshttps://doi.org/10.1177/87552930241290485openalex-snapshot

Data‐Driven Insights Into Post‐Earthquake Reconnaissance Findings: 2023 Türkiye Earthquake Sequence

inferred← citeshttps://doi.org/10.14801/jkiit.2025.23.2.253openalex-snapshot

A Distributed File Management System for Machine Learning Workflow Automation

inferred← citeshttps://doi.org/10.1613/jair.1.14340openalex-snapshot

Towards Green Automated Machine Learning: Status Quo and Future Directions

inferred← citeshttps://doi.org/10.18421/tem112-20openalex-snapshot

A Systematic Literature Review on Multi-Label Classification based on Machine Learning Algorithms

inferred← citeshttps://doi.org/10.21203/rs.3.rs-4172933/v1openalex-snapshot

A practical evaluation of AutoML tools for binary, multiclass, and multilabel classification

inferred← citeshttps://doi.org/10.2139/ssrn.7266101openalex-snapshot

From Data to Decision: An Evolutionary Data-Centric AutoML Framework for Efficient and Lightweight Pipelines

inferred← citeshttps://doi.org/10.2174/0118741207281491240118060019openalex-snapshot

Artificial Intelligence Approaches in Healthcare Informatics Toward Advanced Computation and Analysis

inferred← citeshttps://doi.org/10.28991/esj-2023-07-04-021openalex-snapshot

Advanced Genetic Programming vs. State-of-the-Art AutoML in Imbalanced Binary Classification

inferred← citeshttps://doi.org/10.31284/j.jasmet.2023.v4i1.4437openalex-snapshot

HOSPITAL LENGTH OF STAY PREDICTION WITH ENSEMBLE LEARNING METHODE

inferred← citeshttps://doi.org/10.3233/ica-240736openalex-snapshot

Multi-label classification with imbalanced classes by fuzzy deep neural networks

inferred← citeshttps://doi.org/10.3390/app12157785openalex-snapshot

Semantic Segmentation of Agricultural Images Based on Style Transfer Using Conditional and Unconditional Generative Adversarial Networks

inferred← citeshttps://doi.org/10.3390/app14209461openalex-snapshot

Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning

inferred← citeshttps://doi.org/10.3390/computers12020026openalex-snapshot

Automatic Evaluation of Neural Network Training Results

inferred← citeshttps://doi.org/10.3390/rs16173190openalex-snapshot

An Efficient Task Implementation Modeling Framework with Multi-Stage Feature Selection and AutoML: A Case Study in Forest Fire Risk Prediction

inferred← citeshttps://doi.org/10.3390/w14233898openalex-snapshot

An Automated Machine Learning Engine with Inverse Analysis for Seismic Design of Dams

inferred← citeshttps://doi.org/10.35741/issn.0258-2724.59.5.5openalex-snapshot

Elevating Software Defect Prediction with a Hybrid AutoGluon-SMOTE Strategy on the NASA Project Dataset

inferred← citeshttps://doi.org/10.35784/acs-2022-7openalex-snapshot

DETECTION OF SOURCE CODE IN INTERNET TEXTS USING AUTOMATICALLY GENERATED MACHINE LEARNING MODELS

inferred← citeshttps://doi.org/10.36227/techrxiv.170619255.52099254/v1openalex-snapshot

Non-expert AI Users Building Machine Learning Models: A Short Survey of AutoML Systems

inferred← citeshttps://doi.org/10.4018/ijitsa.353439openalex-snapshot

Enhancing Car Segmentation for Thailand's Expressway Industry With an Automated Hybrid Machine Learning Framework

inferred← citeshttps://doi.org/10.4108/eetsis.4550openalex-snapshot

Comparative analysis of performance of AutoML algorithms: Classification model of payment arrears in students of a private university

inferred← citeshttps://doi.org/10.48550/arxiv.2109.04744openalex-snapshot

Automated Machine Learning, Bounded Rationality, and Rational Metareasoning

inferred← citeshttps://doi.org/10.52783/jes.1377openalex-snapshot

Retracted

inferred← citeshttps://doi.org/10.5753/eniac.2023.233843openalex-snapshot

Exploring Supervised Learning Models for Multi-Label Text Classification in Brazilian Restaurant Reviews

inferred← citeshttps://doi.org/10.7717/peerj.19645openalex-snapshot

Update of machine learning for ultrasound diagnosis of metabolic dysfunction-associated steatotic liver disease: a bright future for deep learning

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.