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Record W3017371359 · doi:10.1016/j.accpm.2020.03.012

Diagnosis and management of heparin-induced thrombocytopenia

2020· article· en· W3017371359 on OpenAlexaff
Yves Gruel, Claire Pouplard, Normand Blais, Pierre Albaladejo, P. Albaladejo, S. Belisle, F. Bonhomme, Annie Borel‐Derlon, J.Y. Borg, J.-L. Bosson, Ariel Cohen, J.-P. Collet, Emmanuel de Maistre, David Faraoni, Pierre Fontana, D. Garrigue Huet, Anne Godiér, Y. Gruel, J. Guay, Jean-Baptiste Hardy, Y. Huet, Brigitte Ickx, Silvy Laporte, Dominique Lasne, J.H. Levy, J. Llau, Grégoire Le Gal, Thomas Lecompte, Sarah Lessire, Dan Longrois, Samia Madi‐Jebara, Emmanuel Marret, J.‐L. Mas, Mikaël Mazighi, Guilherme Pereira Corrêa Meyer, P. Mismetti, Pierre‐Emmanuel Morange, S. Motte, François Mullier, N. Nathan, Philippe Nguyên, Yves Ozier, Gilles Pernod, Nadia Rosencher, Stéphanie Roullet, P.-M. Roy, Charles Marc Samama, S. Schlumberger, Jean‐François Schved, Piérre Siè, A. Steib, Sophie Susen, Sophie Testa, Éric Van Belle, Philipp Linden, André Vincentelli, P. Zufferey

Bibliographic record

VenueAnaesthesia Critical Care & Pain Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsUniversity of OttawaCentre Hospitalier Universitaire Sainte-JustineCentre Hospitalier de l’Université de Montréal
FundersLEO PharmaBayer HealthCareSanofiPfizerDaiichi Sankyo EuropeBristol-Myers Squibb
KeywordsMedicineHeparin-induced thrombocytopeniaHeparinIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

§ Proposal from the French Working on Perioperative Haemostasis (Groupe d'inte ´re ˆt en he ´mostase pe ´riope ´ratoire [GIHP]) and the French Study Group on Thrombosis and Haemostasis (Groupe d'e ´tude sur l'he ´mostase et la thrombose [GFHT]), in collaboration with the French Society of Anaesthesia and Intensive Care Medicine (Socie ´te ´franc ¸aise d'anesthe ´sie et de re ´animation [SFAR]).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.076
GPT teacher head0.345
Teacher spread0.269 · 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 designNot applicable
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

Citations85
Published2020
Admission routes1
Has abstractyes

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