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Living systematic review: 1. Introduction—the why, what, when, and how

2017· article· en· W2754736027 on OpenAlexaff
Julian Elliott, Anneliese Synnot, Tari Turner, Mark Simmonds, Elie A. Akl, Steve McDonald, Georgia Salanti, Joerg J Meerpohl, Harriet MacLehose, John Hilton, David Tovey, Ian Shemilt, James Thomas, Thomas Agoritsas, Caroline Perron, Rebecca K Hodder, Charlotte Pestridge, Lauren Albrecht, Tanya Horsley, Joanne Platt, Rebecca Armstrong, Phi Hùng Nguyễn, Robert M. Plovnick, Anneliese Arno, Noah Ivers, Gail Quinn, Agnes Au, Renea V Johnston, Gabriel Rada, Matthew K. Bagg, Arwel W. Jones, Philippe Ravaud, Catherine Boden, Lara A Kahale, Bernt Richter, Isabelle Boisvert, Homa Keshavarz, Rebecca Ryan, Linn Brandt, Stephanie A. Kolakowsky‐Hayner, Dina H. Salama, Alexandra Bražinová, Sumanth Kumbargere Nagraj, Rachelle Buchbinder, Toby J Lasserson, Lina Santaguida, Chris Champion, Rebecca Lawrence, Nancy Santesso, Jackie Chandler, Zbigniew Leś, Holger J. Schünemann, Andreas Charidimou, Stefan Leucht, Roger Chou, Nicola Low, Diana Sherifali, Rachel Churchill, Andrew I.R. Maas, Reed Siemieniuk, Maryse C. Cnossen, Marie-Joëlle Cossi, Malcolm Macleod, Nicole Skoetz, Michel Jacques Counotte, Iain Marshall, Karla Soares‐Weiser, Samantha Craigie, Velandai Srikanth, Philipp Dahm, Nicole Martin, Katrina Sullivan, Alanna Danilkewich, Laura Martínez García, Kristen Danko, Chris Mavergames, Mark Taylor, Emma Donoghue, Lara Maxwell, Kris Thayer, Corinna Dressler, James H. McAuley, Cathy Egan, Roger Tritton, Joanne E. McKenzie, Guy Tsafnat, Sarah A. Elliott, Peter Tugwell, Itziar Etxeandia‐Ikobaltzeta, Bronwen Merner, Alexis F. Turgeon, Robin Featherstone, Stefania Mondello, Ruth Foxlee, Richard Morley, Gert van Valkenhoef, Paul Garner, Marcus R. Munafò, Per Olav Vandvik, Martha Gerrity, Zachary Munn, Byron Wallace, Paul Glasziou, Melissa Murano, S Wallace, Sally Green, Kristine Newman, Chris Watts, Jeremy Grimshaw, Robby Nieuwlaat, Laura Weeks, Kurinchi Selvan Gurusamy, Adriani Nikolakopoulou, Aaron Weigl, Neal Haddaway, Anna H Noel-Storr, George Wells, Lisa Hartling, Annette M. O’Connor, Wojtek Wiercioch, Jill A. Hayden, Matthew J. Page, Luke Wolfenden, Mark Helfand, Juan José Yepes-Núñez, Julian P. T. Higgins, Jordi Pardo Pardo, Jennifer Yost, Sophie Hill, Leslea Pearson

Bibliographic record

VenueJournal of Clinical Epidemiology · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversityImpact
FundersNational Health and Medical Research CouncilMedical Research CouncilNational Centre for the Replacement, Refinement and Reduction of Animals in Research
KeywordsSystematic reviewCurrencyResource (disambiguation)Risk analysis (engineering)Computer scienceData scienceMedicineManagement scienceMEDLINEEconomicsPolitical scienceMacroeconomics

Abstract

fetched live from OpenAlex
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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.068
metaresearch head score (Gemma)0.209
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.932
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.209
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0050.006
Science and technology studies0.0010.008
Scholarly communication0.0090.020
Open science0.0040.006
Research integrity0.0120.014
Insufficient payload (model declined to judge)0.0120.005

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 head0.886
GPT teacher head0.652
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainMethods
GenreMethods

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

Citations671
Published2017
Admission routes1
Has abstractno

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