MétaCan
Menu
← Back to cohort
Record W2463096213

Advanced Biomedical Ultrasound Imaging and Therapy Laboratory

2016· article· en· W2463096213 on OpenAlexafffundvenueabout
Jahangir Tavakkoli, Raffi Karshafian, Michael C. Kolios

Bibliographic record

VenueCanadian acoustics · 2016
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsToronto Metropolitan University
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchTerry Fox FoundationOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsUltrasoundDiagnostic ultrasoundUltrasound imagingMedical physicsScope (computer science)Therapeutic ultrasoundMedicineBiomedical engineeringPreclinical researchEngineeringComputer scienceRadiology
DOInot available

Abstract

fetched live from OpenAlex

Laboratoire avancée de l'imagerie et de thérapie biomédicale à ultrasons (ABUITL) est un laboratoire de recherche 1600 pieds carrés affilié conjointement à l'Université Ryerson et l'Hôpital St. Michael.Il est l'un des principaux laboratoires de recherche dans le domaine d'ultrasons biomédicale au Canada.Le laboratoire a été créé en 2007 dans le Département de physique de l'Université Ryerson et a été transféré à iBEST (institut de génie biomédical, sciences et technologie) dans l'Hôpital St. Michael en Septembre 2015.Le laboratoire accueille un éventail d'équipements de recherche d'ultrasons biomédicale dans les domaines diagnostic et thérapeutique, et a été actif dans la conduite de projets et la formation de personnel hautement qualifié (PHQ).Champ d'application des projets de recherche dans le laboratoire étend de la compréhension de la science fondamentale et l'investigation des mécanismes biophysiques à de nouvelles applications cliniques dans tous les principaux domaines d'ultrasons biomédicale.

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)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0540.029

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 head0.004
GPT teacher head0.187
Teacher spread0.183 · 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

Citations0
Published2016
Admission routes4
Has abstractyes

Explore more

Same venueCanadian acoustics→Same topicUltrasound and Hyperthermia Applications→French-language works237,207→