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Mortality from snakebite envenomation: an analysis from the Global Burden of Disease Study 2019
Nicholas L S Roberts, Emily K. Johnson, Scott Zeng, Erin B Hamilton, Amir Abdoli, Fares Alahdab, Vahid Alipour, Robert Ancuceanu, Cătălina Liliana Andrei, Davood Anvari, Jalal Arabloo, Marcel Ausloos, Atalel Fentahun Awedew, Ashish Badiye, Shankar M Bakkannavar, Ashish Bhalla, Nikha Bhardwaj, Pankaj Bhardwaj, Soumyadeep Bhaumik, Ali Bijani, Archith Boloor, Tianji Cai, Félix Carvalho, Dinh‐Toi Chu, Rosa A S Couto, Xiaochen Dai, Abebaw Alemayehu Desta, Hoa Do, Lucas Earl, Aziz Eftekhari, Firooz Esmaeilzadeh, Farshad Farzadfar, Eduarda Fernandes, Irina Filip, Masoud Foroutan, Richard C. Franklin, Abhay Gaidhane, Birhan Gebresillassie Gebregiorgis, Berhe Gebremichael, Ahmad Ghashghaee, Mahaveer Golechha, Samer Hamidi, Syed Arefinul Haque, Khezar Hayat, Claudiu Herţeliu, Olayinka Stephen Ilesanmi, M. Mofizul Islam, Jagnoor Jagnoor, Tanuj Kanchan, Neeti Kapoor, Ejaz Ahmad Khan, Mahalaqua Nazli Khatib, Roba Khundkar, Kewal Krishan, G Anil Kumar, Nithin Kumar, Iván Landires, Stephen S Lim, Mohammed Madadin, Venkatesh Maled, Navid Manafi, Laurie B. Marczak, Ritesh G. Menezes, Tuomo J Meretoja, Ted R. Miller, Abdollah Mohammadian-Hafshejani, Ali A Mokdad, Francis N.P. Monteiro, Maryam Moradi, Vinod C Nayak, Cuong Tat Nguyen, Huong Lan Thi Nguyen, Virginia Núñez-Samudio, Samuel M Ostroff, Jagadish Rao Padubidri, Hai Quang Pham, Marina Pinheiro, Majid Pirestani, Quazi Syed Zahiruddin, Navid Rabiee, Amir Radfar, Vafa Rahimi‐Movaghar, Sowmya R. Rao, Prateek Rastogi, David Laith Rawaf, Salman Rawaf, Robert C. Reiner, Amirhossein Sahebkar, Abdallah M Samy, Monika Sawhney, David C. Schwebel, Subramanian Senthilkumaran, Masood Ali Shaikh, Valentin Yurievich Skryabin, Anna Aleksandrovna Skryabina, Amin Soheili, Mark A. Stokes, Rekha Thapar, Marcos Roberto Tovani‐Palone, Bach Xuan Tran, Ravensara S. Travillian, Diana Zuleika Velazquez, Zhi‐Jiang Zhang, Mohsen Naghavi, Rakhi Dandona, Lalit Dandona, Spencer L James, David M. Pigott, Christopher Murray, Simon I Hay, Theo Vos, Sok King Ong
Bibliographic record
VenueResearch Square · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVenomous Animal Envenomation and Studies
Canadian institutionsInstitute of Health Economics
FundersSecretaría Nacional de Ciencia, Tecnología e InnovaciónUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si InovariiFundação para a Ciência e a TecnologiaApplied Molecular Biosciences UnitMinistério da Ciência, Tecnologia e Ensino Superior
KeywordsEnvenomationBurden of diseaseDiseaseMedicineTropical diseaseEnvironmental healthIntensive care medicineInternal medicineBiologyFisheryVenom
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.982
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.058
GPT teacher head0.401
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations6
Published2021
Admission routes1
Has abstractno