Bibliographic record
Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
FundersOffice of Naval ResearchInstitute of Computing Technology, Chinese Academy of SciencesUniversity of California, IrvineUniversity at BuffaloUniversity of North Carolina at Chapel HillUniversity of Colorado BoulderUniversity of Illinois at Urbana-ChampaignStony Brook UniversityShanghaiTech UniversityStockholms UniversitetUniversity of Science and Technology of ChinaUniversität Duisburg-EssenUniversidade Federal do Rio de JaneiroSoochow UniversityClermont UniversitéUniversidade Federal de Minas GeraisWichita State UniversityUniversity of MissouriTsinghua UniversityUniversidad Carlos III de MadridSoutheast UniversityNanjing UniversityIndian Institute of Technology BombayCentral South UniversityTechnische Universität MünchenNational Chiao Tung UniversityUniversity of Electronic Science and Technology of ChinaNational and Kapodistrian University of AthensMcMaster UniversityBen-Gurion University of the NegevChinese University of Hong KongTianjin UniversityHong Kong Polytechnic UniversityHunan UniversitySapienza Università di RomaBinghamton UniversityShanghai Jiao Tong UniversityUniversity of ConnecticutPennsylvania State UniversitySimon Fraser UniversityUniversità degli Studi di PadovaYonsei UniversityDalian University of TechnologyConcordia UniversityIndiana University-Purdue University IndianapolisZhejiang UniversityWorcester Polytechnic InstituteAalto-YliopistoQueen's UniversityBeijing Institute of TechnologyUniversità degli Studi di BresciaAjou UniversityClemson UniversityChung-Ang UniversityChinese Academy of SciencesResearch Institute, Georgia Institute of TechnologyUniversity of SussexNew York Institute of TechnologyTowson UniversityPurdue UniversityTemple UniversityUlsan National Institute of Science and TechnologyKorea Advanced Institute of Science and TechnologyUniversity of AlbertaTechnische Universität KaiserslauternUniversity of Texas at ArlingtonUniversity of Texas at San AntonioGeorgia State UniversityVirginia Commonwealth UniversityUniversity of EdinburghPeking UniversityKU LeuvenUniversity of Massachusetts BostonSeoul National UniversityUniversity of South CarolinaShandong UniversityNanyang Technological UniversityTexas Christian UniversityBirla Institute of Technology and Science, PilaniKungliga Tekniska HögskolanUniversity of PittsburghIowa State UniversityAthens University of Economics and BusinessKorea UniversityCarnegie Mellon UniversityNanjing University of Aeronautics and AstronauticsUniversity of Central FloridaGeorge Washington UniversityUniversity of South FloridaShanghai Educational Development FoundationFlorida International UniversityNational Institute of InformaticsCase Western Reserve UniversityMicrosoft Research AsiaCity University of Hong KongNational Taiwan UniversityUniversity of CreteArizona State UniversityColorado School of MinesUniversity of MinnesotaBudapesti Műszaki és Gazdaságtudományi EgyetemOhio State UniversityUniversità di PisaTechnische Universität DresdenUniversity of New South WalesUniversity of OregonTechnische Universiteit DelftUniversité de LorraineMicrosoft ResearchTexas State UniversityUniversity of Hong KongHuazhong University of Science and TechnologyUniversity of Nebraska-LincolnHelsingin YliopistoCisco SystemsTU Graz, Internationale Beziehungen und MobilitätsprogrammePrinceton UniversityHong Kong Baptist UniversityAuburn UniversityUniversity of GlasgowYork UniversityGeorge Mason University
KeywordsComputer science
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 machine prediction
Teacher imitationNot 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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.194
Threshold uncertainty score0.277
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.806 | 0.602 |
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 head0.060
GPT teacher head0.323
Teacher spread0.263 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
Study designNot applicable
Domainnot available
GenreOther
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
Citations0
Published2023
Admission routes1
Has abstractno