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Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021
Kanyin Liane Ong, Lauryn K Stafford, Susan A. McLaughlin, Edward J. Boyko, Amanda Smith, Bronte Dalton, J Duprey, Jessica A Cruz, Hailey Hagins, Paulina A Lindstedt, Amirali Aali, Yohannes Abate, Melsew Dagne Abate, Mohammadreza Abbasian, Zeinab Abbasi-Kangevari, Mohsen Abbasi‐Kangevari, Samar Abd ElHafeez, Rami Abd‐Rabu, Deldar Morad Abdulah, Abu Yousuf Md Abdullah, Vida Abedi, Hassan Abidi, Richard Gyan Aboagye, Hassan Abolhassani, Eman Abu‐Gharbieh, Ahmed Abu‐Zaid, Tigist Demssew Adane, Isaac Yeboah Addo, Oyelola A. Adegboye, Victor Adekanmbi, Victor Abiola Adepoju, Qorinah Estiningtyas Sakilah Adnani, Rotimi Felix Afolabi, Gina Agarwal, Zahra Babaei Aghdam, Marcela Agudelo‐Botero, Constanza Elizabeth Aguilera Arriagada, Williams Agyemang‐Duah, Bright Opoku Ahinkorah, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmad, Ali Ahmadi, Keivan Ahmadi, Ayman Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ahmed, Marjan Ajami, Rufus Akinyemi, Hanadi Al Hamad, Syed Mahfuz Al Hasan, Tareq Mohammed Ali AL-Ahdal, Tariq A. Alalwan, Ziyad Al‐Aly, Mohammad T AlBataineh, Jacqueline Elizabeth Alcalde‐Rabanal, Sharifullah Alemi, Hassam Ali, Tahereh Alinia, Syed Mohamed Aljunid, Sami Almustanyir, Rajaa Al‐Raddadi, Nelson Alvis‐Guzmán, Firehiwot Amare, Edward Kwabena Ameyaw, Sohrab Amiri, Ganiyu Adeniyi Amusa, Cătălina Liliana Andrei, Ranjit Mohan Anjana, Adnan Ansar, Golnoosh Ansari, Alireza Ansari‐Moghaddam, Anayochukwu Edward Anyasodor, Jalal Arabloo, Aleksandr Y. Aravkin, Demelash Areda, Hidayat Arifin, Mesay Arkew, Benedetta Armocida, Johan Ärnlöv, Anton A Artamonov, Judie Arulappan, Raphael Taiwo Aruleba, Ashokan Arumugam, Zahra Aryan, Mulu Tiruneh, Mohammad Asghari Jafarabadi, Elaheh Askari, Daniel Asmelash, Thomas Astell‐Burt, Mohammad Athar, Seyyed Shamsadin Athari, Maha Atout, Leticia Ávila‐Burgos, Ahmed Awaisu, Sina Azadnajafabad, B B Darshan, Hassan Babamohamadi, Muhammad Badar, Alaa Badawi, Ashish Badiye, Nayereh Baghcheghi, Nasser Bagheri, Sara Bagherieh, Sulaiman Bah, Saeed Bahadory, Ruhai Bai, Atif Amin Baig, Ovidiu Constantin Baltatu, Hamid Reza Baradaran, Martina Barchitta, Mainak Bardhan, Noël C. 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Benseñor, Kidanemaryam Berhe, Alemshet Yirga Berhie, Sonu Bhaskar, Ajay Nagesh Bhat, Jasvinder Singh Bhatti, Boris Bikbov, Faiq Bilal, Bagas Suryo Bintoro, Saeid Bitaraf, Veera Raghavulu Bitra, Vesna Bjegović-Mikanović, Virgínia Bodolica, Archith Boloor, Michael Bräuer, Javier Brazo‐Sayavera, Hermann Brenner, Zahid A Butt, Daniela Călina, Luciana Aparecida Campos, Ismael Campos‐Nonato, Yin Cao, Chao Cao, Josip Car, Márcia Carvalho, Carlos A Castañeda-Orjuela, Ferrán Catalá-López, Ester Cerin, Joshua Chadwick, Eeshwar K Chandrasekar, Gashaw Sisay Chanie, Jaykaran Charan, Vijay Kumar Chattu, Kirti Chauhan, Huzaifa Ahmad Cheema, Endeshaw Chekol Abebe, Simiao Chen, Nicolas Cherbuin, Fatemeh Chichagi, Saravana Babu Chidambaram, William C. Cho, Sonali G Choudhari, Rajiv Chowdhury, E. Chowdhury, Dinh‐Toi Chu, Isaac Sunday Chukwu, Sheng‐Chia Chung, Kaleb Coberly, Alyssa Columbus, Daniela Contreras, Ewerton Cousin, Michael H Criqui, Natália Martins, Sarah Cuschieri, Bashir Dabo, Omid Dadras, Xiaochen Dai, Albertino Damasceno, Rakhi Dandona, Lalit Dandona, Saswati Das, Ana Maria Dascălu, Nihar Ranjan Dash, Mohsen Dashti, Claudio Alberto Dávila-Cervantes, Vanessa De la Cruz‐Góngora, Gebiso Roba Debele, Kourosh Delpasand, Fitsum Wolde Demisse, Getu Debalkie Demissie, Xin Deng, Edgar Denova‐Gutiérrez, Salil V. Deo, Emina Dervišević, Hardik Dineshbhai Desai, Aragaw Tesfaw Desale, Anteneh Mengist Dessie, Fikreab Desta, Syed Masudur Rahman Dewan, Kuldeep Dhama, Meghnath Dhimal, Nancy Diao, Daniel Díaz, Monica Dinu, Mengistie Diress, Shirin Djalalinia, Linh Phuong Doan, Deepa Dongarwar, Francisco Winter dos Santos Figueiredo, Bruce Bartholow Duncan, Siddhartha Dutta, Arkadiusz Dziedzic, Hisham Atan Edinur, Michael Ekholuenetale, Temitope Cyrus Ekundayo, Islam Y. 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Gautam, Mesfin Gebrehiwot, Kahsu Gebrekirstos Gebrekidan, Teferi Gebru Gebremeskel, Lemma Getacher, Fataneh Ghadirian, Seyyed‐Hadi Ghamari, Mohammad Ghasemi Nour, Fariba Ghassemi, Mahaveer Golechha, Pouya Goleij, Davide Golinelli, Sameer Vali Gopalani, Habtamu Alganeh Guadie, Shi‐Yang Guan, Temesgen Worku Gudayu, Rafael Alves Guimarães, Rashid Abdi Guled, Kartik Gupta, Veer Bala Gupta, Vivek Gupta, Bishal Gyawali, Rasool Haddadi, Najah R Hadi, Teklehaimanot Gereziher Haile, Ramtin Hajibeygi, Arvin Haj‐Mirzaian, Rabih Halwani, Samer Hamidi, Graeme J. Hankey, Md. Abdul Hannan, Shafiul Haque, Hamid Harandi, Netanja I. Harlianto, S M Mahmudul Hasan, Syed Shahzad Hasan, Hamidreza Hasani, Soheil Hassanipour, Mohammed Bheser Hassen, Johannes Haubold, Khezar Hayat, Golnaz Heidari, Mohammad Heidari, Kamran Hessami, Yuta Hiraike, Ramesh Holla, Sahadat Hossain, Md Shakhaoat Hossain, Mohammad‐Salar Hosseini, Mehdi Hosseinzadeh, Hassan Hosseinzadeh, Junjie Huang, Md. 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Karaye, Samad Karkhah, Patrick DMC Katoto, Navjot Kaur, Sina Kazemian, Sewnet Adem Kebede, Yousef Khader, Himanshu Khajuria, Amirmohammad Khalaji, Moien AB Khan, Maseer Khan, Ajmal Khan, Saval Khanal, Moawiah Khatatbeh, Amir M Khater, Sorour Khateri, Fatemeh Khorashadizadeh, Jagdish Khubchandani, Biruk Getahun Kibret, Min Seo Kim, Ruth W Kimokoti, Adnan Kısa, Mika Kivimäki, Ali‐Asghar Kolahi, Somayeh Komaki, Farzad Kompani, Hamid Reza Koohestani, Oleksii Korzh, Karel Kostev, Nikhil Kothari, Ai Koyanagi, Kewal Krishan, Yuvaraj Krishnamoorthy, Barthélémy Kuate Defo, Mohammed Kuddus, Md Abdul Kuddus, Harish Kumar, Satyajit Kundu, Maria Dyah Kurniasari, Ambily Kuttikkattu, Carlo La Vecchia, Tea Lallukka, Bagher Larijani, Anders Larsson, Kamaluddin Latief, Basira Kankia Lawal, Thao T. Le, Trang Thi Bich Le, Shaun Wen Huey Lee, Munjae Lee, Wei‐Chen Lee, Paul H. Lee, Sang-woong Lee, Seung Won Lee, Samson Mideksa Legesse, Jacopo Lenzi, Yongze Li, Ming‐Chieh Li, Stephen S Lim, Lee‐Ling Lim, Xuefeng Liu, Chaojie Liu, Chun‐Han Lo, Graciliana Lopes, Stefan Lorkowski, Rafael Lozano, Giancarlo Lucchetti, Azzam A. Maghazachi, Phetole Walter Mahasha, Mansour Adam Mahmoud, Razzagh Mahmoudi, Marzieh Mahmoudimanesh, Azeem Majeed, Pantea Majma Sanaye, Konstantinos C. Makris, Kashish Malhotra, Ahmad Azam Malik, Iram Malik, Tauqeer Hussain Mallhi, Déborah Carvalho Malta, Abdullah Al Mamun, Borhan Mansouri, Hamid Reza Marateb, Parham Mardi, Santi Martini, Miquel Martorell, Roy Rillera Marzo, Reza Masoudi, Sahar Masoudi, Elezebeth Mathews, Andrea Maugeri, Giampiero Mazzaglia, Teferi Mekonnen, Mahboobeh Meshkat, Tomislav Meštrović, Junmei Miao Jonasson, Tomasz Miazgowski, Irmina Maria Michałek, Le Huu Nhat Minh, GK Mini, J. Jaime Miranda, Reza Mirfakhraie, Erkin М Мirrakhimov, Mohammad Mirza‐Aghazadeh‐Attari, Kebede Haile Misgina, Manish Mishra, Babak Moazen, Nouh Saad Mohamed, Esmaeil Mohammadi, Mohsen Mohammadi, Abdollah Mohammadian-Hafshejani, Marita Mohammadshahi, Alireza Mohseni, Hoda Mojiri-Forushani, Ali H. Mokdad, Sara Momtazmanesh, Lorenzo Monasta, Md. Moniruzzaman, Ute Mons, Fateme Montazeri, AmirAli Moodi Ghalibaf, Yousef Moradi, Maryam Moradi, Mostafa Moradi Sarabi, Negar Morovatdar, Shane D. Morrison, Jakub Morze, Elías Mossialos, Ebrahim Mostafavi, Ulrich Müeller, Francesk Mulita, Admir Mulita, Efrén Murillo‐Zamora, Kamarul Imran Musa, Julius Chacha Mwita, Shankar Prasad Nagaraju, Mohsen Naghavi, Firzan Nainu, Tapas Sadasivan Nair, Hastyar Hama Rashid Najmuldeen, Vinay Nangia, Shumaila Nargus, Abdallah Y. Naser, Hasan Nassereldine, Zuhair S. Natto, Javaid Nauman, Biswa Prakash Nayak, Rawlance Ndejjo, Hadush Negash, Ruxandra Irina Negoi, Hau Thi Hien Nguyen, Dang Nguyen, Phat Tuan Nguyen, Văn Thành Nguyễn, Robina Khan Niazi, Yeshambel T. Nigatu, Dina Nur Anggraini Ningrum, Muhammad A Nizam, Lawrence Achilles Nnyanzi, Mamoona Noreen, Jean Jacques Noubiap, Ogochukwu Janet Nzoputam, Chimezie Igwegbe Nzoputam, Bogdan Oancea, Nkechi Martina Odogwu, Oluwakemi Ololade Odukoya, Vivek Anand Ojha, Hassan Okati‐Aliabad, Akinkunmi Paul Okekunle, Osaretin Christabel Okonji, Patrick Godwin Okwute, Isaac Iyinoluwa Olufadewa, Obinna Onwujekwe, Michał Ordak, Alberto Ortíz, Uchechukwu Levi Osuagwu, Abderrahim Oulhaj, Mayowa Owolabi, Alicia Padrón‐Monedero, Jagadish Rao Padubidri, Raffaele Palladino, Demosthenes B. Panagiotakos, Songhomitra Panda‐Jonas, Ashok Pandey, Anamika Pandey, Seithikurippu R. Pandi‐Perumal, Anca Pantea Stoian, Shahina Pardhan, Tarang Parekh, Utsav Parekh, Maja Pasovic, Jay Patel, Jenil Patel, Uttam Paudel, Veincent Christian Filipino Pepito, Marcos Pereira, Norberto Perico, Simone Perna, Ionela-Roxana Petcu, Fanny Emily Petermann-Rocha, Vivek Podder, Maarten J. Postma, Ghazaleh Pourali, Naeimeh Pourtaheri, Elton Junio Sady Prates, Mirza Muhammad Fahd Qadir, Ibrahim Qattea, Pourya Raee, Ibrar Rafique, Mehran Rahimi, Mahban Rahimifard, Vafa Rahimi‐Movaghar, Obaidur Rahman, Muhammad Aziz Rahman, Mohammad Hifz Ur Rahman, Mosiur Rahman, Md. Mosfequr Rahman, Mohamed Rahmani, Shayan Rahmani, Vahid Rahmanian, Setyaningrum Rahmawaty, Niloufar Rahnavard, Bibek Rajbhandari, Pradhum Ram, Sheena Ramazanu, Juwel Rana, Nemanja Rančić, Muhammad Modassar Ali Nawaz Ranjha, Chythra R Rao, Deepthi Rapaka, Drona Rasali, Sina Rashedi, Vahid Rashedi, Ahmed Mustafa Rashid, Mohammad‐Mahdi Rashidi, Zubair Ahmed Ratan, Salman Rawaf, Lal Rawal, Elrashdy M. Redwan, Giuseppe Remuzzi, Kannan R. R. Rengasamy, André M. N. Renzaho, Luis Felipe Reyes, Nima Rezaei, Nazila Rezaei, Mohsen Rezaeian, Hossein Rezazadeh, Seyed Mohammad Riahi, Yohanes Andy Rias, Muhammad Riaz, Daniela Ribeiro, Mónica Rodrigues, Jefferson Antonio Buendía, Leonardo Roever, Peter Rohloff, Gholamreza Roshandel, Abazar Roustazadeh, Godfrey Mutashambara Rwegerera, Aly M A Saad, Maha Saber-Ayad, Siamak Sabour, Leila Sabzmakan, Basema Saddik, Erfan Sadeghi, Umar Saeed, Sahar Saeedi Moghaddam, Sare Safi, Sher Zaman Safi, Amene Saghazadeh, Narjes Saheb Sharif‐Askari, Fatemeh Saheb Sharif‐Askari, Amirhossein Sahebkar, Soumya Swaroop Sahoo, Harihar Sahoo, KM Saif‐Ur‐Rahman, Mirza Rizwan Sajid, Sarvenaz Salahi, Saina Salahi, Mohamed A. Saleh, Mohammad Amin Salehi, Joshua A. Salomon, Juan Sanabria, Rama Krishna Sanjeev, Francesco Sanmarchi, Milena M Santric-Milicevic, Made Ary Sarasmita, Saman Sargazi, Brijesh Sathian, Thirunavukkarasu Sathish, Monika Sawhney, Markus P. Schlaich, María Inês Schmidt, Art Schuermans, Abdul-Aziz Seidu, Nachimuthu Senthil Kumar, Sadaf G Sepanlou, Yashendra Sethi, Allen Seylani, Maryam Shabani, Tahereh Shafaghat, Melika Shafeghat, Mahan Shafie, Nilay S. Shah, Samiah Shahid, Masood Ali Shaikh, Mohd Shanawaz, Mohammed Shannawaz, Sadaf Sharfaei, Bereket Beyene Shashamo, Rahman Shiri, Aminu Shittu, K. M. Shivakumar, Siddharudha Shivalli, Parnian Shobeiri, Fereshteh Shokri, Kerem Shuval, Migbar Mekonnen Sibhat, Luís R. Silva, Colin R Simpson, Ambrish Singh, Paramdeep Singh, Surjit Singh, Md Shahjahan Siraj, Anna Aleksandrovna Skryabina, Abdullah Al Mamun Sohag, Hamidreza Soleimani, Solikhah Solikhah, Mohammad Sadegh Soltani‐Zangbar, Ranjani Somayaji, Reed J D Sorensen, А. В. Стародубова, Sujata Sujata, Muhammad Suleman, Jing Sun, Johan Sundström, Rafael Tabarés‐Seisdedos, Seyyed Mohammad Tabatabaei, Seyed‐Amir Tabatabaeizadeh, Mohammad Tabish, Majid Taheri, Ensiyeh Taheri, Elahe Taki, Jacques Lukenze Tamuzi, Ker‐Kan Tan, Nathan Y Tat, Birhan Tsegaw Taye, Worku Animaw Temesgen, Mohamad‐Hani Temsah, Riki Tesler, Pugazhenthan Thangaraju, Rajshree Thapa, Samar Tharwat, Nihal Thomas, Jansje Henny Vera Ticoalu, Amir Tiyuri, Marcello Tonelli, Marcos Roberto Tovani‐Palone, Domenico Tricò, Indang Trihandini, Jaya Prasad Tripathy, Samuel Tromans, Abdul Rohim Tualeka, Derara Girma Tufa, Stefanos Tyrovolas, Sana Ullah, Era Upadhyay, Seyed Mohammad Vahabi, Asokan Govindaraj Vaithinathan, Rohollah Valizadeh, Kim Robin van Daalen, Priya Vart, Shoban Babu Varthya, Tommi Vasankari, Siavash Vaziri, Madhur Verma, Georgios‐Ioannis Verras, Danh Cao Vo, Birhanu Wagaye, Yasir Waheed, Ziyue Wang, Yanqing Wang, Cong Wang, Fang Wang, Gizachew Tadesse Wassie, Melissa Y. Wei, Ronny Westerman, Nuwan Darshana Wickramasinghe, Yifan Wu, Ratna Dwi Wulandari, Juan Xia, Hong Xiao, Suowen Xu, Xiaoyue Xu, Dereje Y Yada, Lin Yang, Hiroshi Yatsuya, Metin Yeşiltepe, Siyan Yi, Hunachew Kibret Yohannis, Naohiro Yonemoto, Yuyi You, Sojib Bin Zaman, Iman Zare, Kourosh Zarea, Armin Zarrintan, Михаил Сергеевич Застрожин, Naod Gebrekrstos Zeru, Zhi-Jiang Zhang, Chenwen Zhong, Jingjing Zhou, Magdalena Zielińska, Yossef Teshome Zikarg, Sanjay Zodpey, Mohammad Zoladl, Zhiyong Zou, Alimuddin Zumla, Yves Miel H Zuñiga, Dianna J. Magliano, Christopher J L Murray, Simon I Hay, Theo Vos
Notice bibliographique
RevueThe Lancet · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueDiabetes, Cardiovascular Risks, and Lipoproteins
Établissements canadiensnon disponible
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Mots-clésBurden of diseaseMedicineDiabetes mellitusDiseaseDisease burdenMEDLINEEnvironmental healthGlobal healthIntensive care medicinePublic healthInternal medicinePolitical sciencePathology
Résumé
BACKGROUND: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. METHODS: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. FINDINGS: In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. INTERPRETATION: Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. FUNDING: Bill & Melinda Gates Foundation.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
score de la tête « metaresearch » (Codex)0,020
score de la tête « metaresearch » (Gemma)0,024
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: Méta-analyse
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,053
Score d'incertitude au seuil0,107
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,020 |
| Bibliométrie | 0,010 | 0,012 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
Tête enseignante Opus0,034
Tête enseignante GPT0,304
Écart entre enseignants0,271 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validation
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeMéta-analyse
Domainenon disponible
GenreEmpirique
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».
En bref
Citations4 238
Publié2023
Routes d'admission1
Résumé présentoui