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Record W2750976195 · doi:10.5281/zenodo.557093

Proceedings Of The 18Th International Conference On Biomedical Applications Of Electrical Impedance Tomography

2017· article· en· W2750976195 on OpenAlexafffund

Bibliographic record

VenueOpenBU/Boston University Institutional Repository (Boston University) · 2017
Typearticle
Languageen
FieldEngineering
TopicElectrical and Bioimpedance Tomography
Canadian institutionsCarleton UniversityUniversity of Ottawa
FundersCongressionally Directed Medical Research ProgramsJapan Society for the Promotion of ScienceEngineering and Physical Sciences Research CouncilMedical Research CouncilNatural Sciences and Engineering Research Council of CanadaDefense Advanced Research Projects AgencyTekesNational Research FoundationBundesministerium für Bildung und ForschungInstrumentariumin TiedesäätiöEuropean CommissionNational Institutes of HealthTürkiye Bilimsel ve Teknolojik Araştırma KurumuVienna Science and Technology FundGlaxoSmithKlineJane ja Aatos Erkon SäätiöConsejo Nacional de Ciencia y TecnologíaNational Science Foundation
KeywordsElectrical impedance tomographyPresentation (obstetrics)Electrical impedanceComputed tomography

Abstract

fetched live from OpenAlex

Proceedings of the 18th International Conference on Biomedical Applications of ELECTRICAL IMPEDANCE TOMOGRAPHY Edited by Alistair Boyle, Ryan Halter, Ethan Murphy, Andy Adler June 21-24, 2017 Thayer School of Engineering at Dartmouth, Hanover, New Hampshire, USA This document is the collection of papers accepted for presentation at the 18th International Conference on Biomedical Applications of Electrical Impedance Tomography. Each individual paper in this collection: © 2017 by the indicated authors. Collected work: © 2017 Alistair Boyle, Ryan Halter, Ethan Murphy, Andy Adler

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)0.004
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.088
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0880.050

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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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
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

Citations7
Published2017
Admission routes2
Has abstractyes

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