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2021· other· en· W4377980854 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsLibrary scienceExcellenceLicenseScholarshipPublishingPolitical scienceLawHistoryComputer science

Abstract

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Extract Oxford University Press is a department of the University of Oxford. It furthersthe University’s objective of excellence in research, scholarship, and educationby publishing worldwide. Oxford is a registered trade mark of Oxford UniversityPress in the UK and certain other countries.Published in the United States of America by Oxford University Press198 Madison Avenue, New York, NY 10016, United States of America.© Oxford University Press 2021All rights reserved. No part of this publication may be reproduced, stored ina retrieval system, or transmitted, in any form or by any means, without theprior permission in writing of Oxford University Press, or as expressly permittedby law, by license, or under terms agreed with the appropriate reproductionrights organization. Inquiries concerning reproduction outside the scope of theabove should be sent to the Rights Department, Oxford University Press, at theaddress above.You must not circulate this work in any other formand you must impose this same condition on any acquirer.Library of Congress Cataloging-in-Publication DataNames: Sikka, Neal, author.Title: A Practical Guide to Emergency Telehealth / editor Neal Sikka.Description: New York, NY : Oxford University Press, [2021] | Includesbibliographical references and index. |Identifiers: LCCN 2021027764 (print) | LCCN 2021027765 (ebook) |ISBN 9780190066475 (paperback) | ISBN 9780190066499 (epub) |ISBN 9780190066505 (online)Subjects: MESH: Telemedicine | Emergency Medical Services | EmergenciesClassification: LCC R855.3 (print) | LCC R855.3 (ebook) | NLM WX 215 |DDC 610.285—dc23LC record available at https://lccn.loc.gov/2021027764LC ebook record available at https://lccn.loc.gov/2021027765DOI: 10.1093/med/9780190066475.001.0001This material is not intended to be, and should not be considered, a substitute for medical or other professional advice. Treatment for the conditions described in this material is highly dependent on the individual circumstances. And, while this material is designed to offer accurate information with respect to the subject matter covered and to be current as of the time it was written, research and knowledge about medical and health issues is constantly evolving and dose schedules for medications are being revised continually, with new side effects recognized and accounted for regularly. Readers must therefore always check the product information and clinical procedures with the most up- to- date published product information and data sheets provided by the manufacturers and the most recent codes of conduct and safety regulation. The publisher and the authors make no representations or warranties to readers, express or implied, as to the accuracy or completeness of this material. Without limiting the foregoing, the publisher and the authors make no representations or warranties as to the accuracy or efficacy of the drug dosages mentioned in the material. The authors and the publisher do not accept, and expressly disclaim, any responsibility for any liability, loss, or risk that may be claimed or incurred as a consequence of the use and/ or application of any of the contents of this material9 8 7 6 5 4 3 2 1Printed by Marquis, Canada

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)0.011
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 score0.114
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0020.001
Scholarly communication0.0120.007
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.8860.834

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 head0.042
GPT teacher head0.369
Teacher spread0.328 · 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; 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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