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Record W3082872684 · doi:10.1111/jth.15094

Anticoagulant interventions in hospitalized patients with COVID‐19: A scoping review of randomized controlled trials and call for international collaboration

2020· review· en· W3082872684 on OpenAlexafffund
Tobias Tritschler, Marie‐Eve Mathieu, Leslie Skeith, Marc Rodger, Saskia Middeldorp, Timothy Brighton, Per Morten Sandset, Susan R. Kahn, Derek Angus, Marc Blondon, Marc J. M. Bonten, Marco Cattaneo, Mary Cushman, Lennie Derde, Maria T. DeSancho, Jean‐Luc Diehl, Ewan C. Goligher, Bernd Jilma, Peter Jüni, Patrick R. Lawler, Marco Marietta, John C. Marshall, Colin McArthur, Carlos Henrique Miranda, Tristan Mirault, Nuccia Morici, Usha Perepu, Christian Schörgenhofer, Michelle Sholzberg, Alex C. Spyropoulos, Steve Webb, Ryan Zarychanski, Stéphane Zuily, Grégoire Le Gal

Bibliographic record

VenueJournal of Thrombosis and Haemostasis · 2020
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsUniversity of ManitobaOttawa HospitalUniversity Health NetworkCancerCare ManitobaJewish General HospitalSt. Michael's HospitalUniversity of TorontoResearch Institute in Oncology and HematologyMcGill UniversityUniversity of OttawaTed Rogers Centre for Heart ResearchUniversity of Calgary
FundersResearch Committee, Aristotle University of ThessalonikiCanadian Institutes of Health ResearchBundesministerium für Bildung, Wissenschaft und ForschungLifeArc
KeywordsMedicineClinical trialRandomized controlled trialPsychological interventionAnticoagulantIntensive care medicineEmergency medicineInternal medicine

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)0.024
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.070
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0170.017
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0030.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.247
GPT teacher head0.556
Teacher spread0.309 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations98
Published2020
Admission routes2
Has abstractno

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