1,721,329 research outputs found
sj-RData-2-dhj-10.1177_20552076231191967 - Supplemental material for A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials
Supplemental material, sj-RData-2-dhj-10.1177_20552076231191967 for A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials by Danila Azzolina, Rosanna Comoretto, Liviana Da Dalt, Silvia Bressan and Dario Gregori in DIGITAL HEALTH</p
sj-docx-1-dhj-10.1177_20552076231191967 - Supplemental material for A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials
Supplemental material, sj-docx-1-dhj-10.1177_20552076231191967 for A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials by Danila Azzolina, Rosanna Comoretto, Liviana Da Dalt, Silvia Bressan and Dario Gregori in DIGITAL HEALTH</p
sj-Rdata-3-dhj-10.1177_20552076231191967 - Supplemental material for A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials
Supplemental material, sj-Rdata-3-dhj-10.1177_20552076231191967 for A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials by Danila Azzolina, Rosanna Comoretto, Liviana Da Dalt, Silvia Bressan and Dario Gregori in DIGITAL HEALTH</p
sj-Rmd-4-dhj-10.1177_20552076231191967 - Supplemental material for A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials
Supplemental material, sj-Rmd-4-dhj-10.1177_20552076231191967 for A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials by Danila Azzolina, Rosanna Comoretto, Liviana Da Dalt, Silvia Bressan and Dario Gregori in DIGITAL HEALTH</p
sj-docx-1-dhj-10.1177_20552076221133696 - Supplemental material for A topic trend analysis on COVID-19 literature
Supplemental material, sj-docx-1-dhj-10.1177_20552076221133696 for A topic trend analysis on COVID-19 literature by Sara Urru, Veronica Sciannameo, Corrado Lanera, Silvano Salaris, Dario Gregori and Paola Berchialla in Digital Health</p
Supplementary_material_MCRR_revised – Supplemental material for Analysis of Unstructured Text-Based Data Using Machine Learning Techniques: The Case of Pediatric Emergency Department Records in Nicaragua
Supplemental material, Supplementary_material_MCRR_revised for Analysis of Unstructured Text-Based Data Using Machine Learning Techniques: The Case of Pediatric Emergency Department Records in Nicaragua by Giulia Lorenzoni, Silvia Bressan, Corrado Lanera, Danila Azzolina, Liviana Da Dalt and Dario Gregori in Medical Care Research and Review</p
sj-docx-1-cpj-10.1177_00099228231220174 – Supplemental material for PICU Admission of Children for Status Epilepticus: Is There a Different Approach Between Referral and Second-Level Hospitals in an Italian Region?
Supplemental material, sj-docx-1-cpj-10.1177_00099228231220174 for PICU Admission of Children for Status Epilepticus: Is There a Different Approach Between Referral and Second-Level Hospitals in an Italian Region? by Claudia Maria Bonardi, Margherita Nosadini, Giulia Lorenzoni, Anna Tessari, Lorenza Santoro, Andrea Pettenazzo, Dario Gregori, Stefano Sartori and Angela Amigoni in Clinical Pediatrics</p
Supplementary_tables - Blood Products Transfusion and Mid-Term Outcomes of Lung Transplanted Patients Under Extracorporeal Membrane Oxygenation Support
Supplementary_tables for Blood Products Transfusion and Mid-Term Outcomes of Lung Transplanted Patients Under Extracorporeal Membrane Oxygenation Support by Tommaso Pettenuzzo, Giulio Faggi, Guido Di Gregorio, Marco Schiavon, Giuseppe Marulli, Dario Gregori, Federico Rea, Carlo Ori, and Paolo Feltracco in Progress in Transplantation</p
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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