Quality assessment of chicken using machine learning and electronic nose by Hassan Anwar, Talha Anwar

“…To evaluate the performance of the machine learning algorithms, different data splitting approaches were tested to understand their impact on model accuracy. Random Forest achieved 100 % accuracy with randomly split data and 69 % accuracy with non-randomly split data. …”
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Fitness landscapes of human microsatellites. by Ryan J Haasl, Bret A Payseur

“…We introduce four general models of natural selection that are each characterized by just two parameters, are easily simulated, and are specifically designed for microsatellites. Using a random forests approach to approximate Bayesian computation, we fit these models to carefully chosen microsatellites genotyped in 200 humans from a diverse collection of eight populations. …”
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Dinâmica da paisagem em planícies de inundação amazônicas: o caso do Lago Grande do Curuai, Pará, Brasil. by Lucas Garcia Magalhães Peres, Helen Gurgel, Anne-Elisabeth Laques

“…Although there is a decrease in dry land forest areas, the class in which there is greater increase is the secondary/"capoeira" vegetation. …”
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Interpretable Machine Learning Techniques for an Advanced Crop Recommendation Model by Mohamed Bouni, Badr Hssina, Khadija Douzi, Samira Douzi

“…Our research addresses this critical imperative by introducing an innovative predictive model that refines crop recommendation systems through advanced machine learning techniques, specifically random forest and SHapley Additive exPlanations (SHAP). This study aims to overcome the limitations of traditional advisory approaches by incorporating interpretability tools, clarifying the model’s decision-making process around specific instances. …”
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Development of a High‐Latitude Convection Model by Application of Machine Learning to SuperDARN Observations by W. A. Bristow, C. A. Topliff, M. B. Cohen

“…The ML algorithm random forests regression was applied to a database of velocities derived from the Super Dual Auroral Radar Network (SuperDARN) observations processed with the potential mapping technique, Map‐Potential (Ruohoniemi & Baker, 1998, https://doi.org/10.1029/98ja01288). …”
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Machine learning analysis of rivaroxaban solubility in mixed solvents for application in pharmaceutical crystallization by Mohammed Alqarni, Ali Alqarni

“…Using a dataset with over 250 data points and including solvents encoded with one-hot encoding, four models were compared: Gradient Boosting (GB), Light Gradient Boosting (LGB), Extra Trees (ET), and Random Forest (RF). The Jellyfish Optimizer (JO) algorithm was applied to tune hyperparameters, enhancing model performance. …”
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Horizontes de la reflexividad etnográfica. Revelaciones y tensiones para el estudio antropológico del desarrollo en Chile by Noelia Carrasco Henríquez

“…Como referente empírico, recogemos el tratamiento etnográfico de la industria forestal y sus circunstancias socioculturales, derivados de la reflexión que antecede y acompaña la ejecución del Proyecto Fondecyt N° 11080196, entre noviembre de 2008 y noviembre de 2010.…”
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Evaporation Rate Prediction Using Advanced Machine Learning Models: A Comparative Study by Zainab Abdulelah Al Sudani, Golam Saleh Ahmed Salem

“…In this study, four machine learning (ML) modeling approaches, extreme learning machine (ELM), gradient boosting machine (GBM), quantile random forest (QRF), and Gaussian process regression (GPR), have been developed to estimate the monthly evaporation loss over two stations located in Iraq. …”
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Analysis of Determinants of Economic Efficiency in Honey Production in Horo Guduru Zone, Ethiopia: Stochastic Dual Cost Frontier Model Approach by Tolesa Tesema, Megersa Adugna

“…The study suggests policies to address economic inefficiencies by increasing the number of hives, extending the best performers’ experience by increasing the frequency of extension contacts on honey production, facilitating and expanding credit service in the study area, making bee forage access simple, and increasing forest coverage on the land area in line with the current policy of Ethiopia. …”
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Operational Risk Assessment for the Pollination Service with Apis mellifera Bees in Cashew Crops in Vichada, Colombia by Lizeth Castro Mercado, Juan José Bravo Bastidas, Juan Carlos Osorio Gómez

“…Such losses have far-reaching consequences, affecting the livelihoods of peasant beekeepers in the region and potentially discouraging the maintenance of bee colonies and forests.…”
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Indicadores PER y FPEIR para el Análisis de la sustentabilidad en el municipio de Cihuatlán, Jalisco, México by Roberto Armando Vázquez-Valencia, Rosa M. García-Almada

“…El trabajo se realizó enfatizando tres sectores: forestal, agropecuario y turístico. La información fue obtenida de documentos oficiales, participación en talleres y entrevistas a actores relevantes, estos últimos ayudaron a identificar los problemas ambientales y realizaron una valoración subjetiva de su estado. …”
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Creation and interpretation of machine learning models for aqueous solubility prediction by Minyi Su, Enric Herrero

“…Results: Among the different ML methods, random forest (RF) models obtain the best performance in the different test sets. …”
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Similarity Index among Acacia mangium, Acacia auriculiformis, and its Hybrid Based on the Anatomical Properties of Root, Stem, and Leaf by Sri Sunarti, Visda Fitriana, Suharyanto Suharyanto

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Computational linguistics and natural language processing techniques for semantic field extraction in Arabic online news by Maulana Ihsan Ahmad, Moh. Kanif Anwari

“…The research evaluated five classification models: Naive Bayes, Support Vector Machine (SVM), Logistic Regression, Random Forest, and Gradient Boosting. Among these, SVM achieves the highest overall accuracy of 90%. …”
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Predictive performance of count regression models versus machine learning techniques: A comparative analysis using an automobile insurance claims frequency dataset. by Gadir Alomair

“…The research involved a comparative evaluation of several models, including Poisson, NB, zero-inflated Poisson (ZIP), hurdle Poisson, zero-inflated negative binomial (ZINB), hurdle negative binomial, random forest (RF), support vector machine (SVM), and artificial neural network (ANN) on an insurance dataset. …”
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Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis by Onur Baser, Gabriela Samayoa, Nehir Yapar, Erdem Baser

“…In addition to the baseline model, a gradient-boosted classification tree, naïve Bayes, and random forest model were created and compared using receiver operator characteristics, area under the curve, and accuracy. …”
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A Chromosome-level genome assembly of the alpine medicinal plant Bergenia purpurascens (Saxifragaceae) by Xue-Die Liu, Alex D. Twyford, Peter M. Hollingsworth, Ya-Huang Luo, Sheng-Ping Ming, Bo-Yun Yang, Lian-Ming Gao, Shao-Lin Tan

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Development of a zoonotic influenza distribution assessment and ranking system (ZIDAR): Technical application in Nepal to support cross-sectoral risk-based surveillance by Adam Charette-Castonguay, Dipendra Gautam, Binay Shrestha, Hemant Chandra Ojha, Barun Kumar Sharma, Mukul Upadhayaya, Sujan Rana, Roshika Shrestha, Lok Bandu Chaudhary, Bhawana Kandel, Rudra Prasad Marasini, Sharmila Chapagain, Tulsi Ram Gompo, Surendra Karki, Apsara Poudel, Saugat Shrestha, Avinash Sunny Kayastha, Arun Kumar Govindakarnavar, Reuben Samuel, Allison Gocotano, Pushpa Ranjan Wijesinghe, Nilesh Buddha, Edwin Ceniza Salvador, Manish Kakkar, Ricardo J. Soares Magalhães

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Kidney Function and Incident Stroke and Dementia Using an Updated Estimated Glomerular Filtration Rate Equation Without Race: The Multi-Ethnic Study of Atherosclerosis by Samuel R. Moen, Jeffrey R. Misialek, Timothy M. Hughes, Craig W. Johnson, Mark J. Sarnak, Sarah N. Forrester, W.T. Longstreth, Jr., Mercedes R. Carnethon, James S. Pankow, Sanaz Sedaghat

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Feasibility, Usability, and Pilot Efficacy Study of a Software-Enabled, Virtual Pulmonary Rehabilitation with Remote Therapeutic Monitoring by Flynn S, Mosher CL, Cornelison S, Rao E, Metzler KA, Pu W, Davies J, Paladenech C, Doyle D, MacIntyre N, Ohar J

“…Paul Sticht Center on Aging and Rehabilitation, Atrium Health Wake Forest Baptist Medical Center, Winston-Salem, North Carolina, USA; 5Wake Forest University School of Medicine, Winston-Salem, North Carolina, USACorrespondence: Sheryl Flynn, Blue Marble Health, 2400 Lincoln Ave, Altadena, CA, 91001, USA, Tel +1 626 296 6400, Email Sheryl@BlueMarbleHealthCo.ComObjective: Fewer than 3% of adults with Chronic Obstructive Pulmonary Disease (COPD) attend in-person, center-based pulmonary rehabilitation (PR) despite demonstrated health benefits and reduction in mortality. …”
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