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Record W4407220134 · doi:10.1503/cjs.000225

C-CASE 2024: Surgical Education Through Innovation01. A 25-year retrospective of Canadian plastic surgery research and its influence: a thorough bibliometric study02. Evaluating knowledge translation applications of a Canadian surgical education app among Saudi Arabian medical trainees03. An educational podcast for trainees to learn about plastic surgery training in Canada — “Doctority Canada: Plastic Surgery.”04. Educational landscape and perspectives on interventional neuroradiology training in residency: a scoping review05. Moving toward collaboration: introducing a pan-Canadian virtual patient initiative06. From classroom to the operating room: equipping medical students for surgical clerkship success through a skills-based workshop07. Participants’ initial reactions and appreciation of ExploreMD, a medical career exploration event in the region of Outaouais, Quebec08. Shoulder dislocation: Health care professionals produce higher-quality content on TikTok09. Weaving our narrative: perspectives from hijab-wearing learners in the operating room10. The impact of extended reality simulators on ophthalmic surgical training and performance: a systematic review and meta-analysis of 17 623 eyes11. Impact of a new bilingual online career orientation tool on medical students12. Examining the utility of LearnENT in undergraduate medical education13. Evaluating the current teaching practices for robotic-assisted surgery training during residency in different surgical programs across Canada14. Early exposure to neurosurgery: assessment of perceptions, expectations, mentorship, representation, and competence on medical student interest in neurosurgery15. Digital scribes in medical education: balancing innovation with skill development across educational levels16. A blueprint for near-peer medical student anatomy tutoring17. Enhancing productivity in medical education research groups: a scoping review18. Generative artificial intelligence in plastic surgery medical education: a quality improvement scoping review19. An in-depth exploration of the entrustable professional activity (EPA) assessment–related emotions of residents and faculty across specialties20. Outcomes of a competency-based microlearning mobile application for surgical residents21. Enhancing clinical clerk surgical preparedness using microlearning modules22. From model to mastery: a randomized study on the effect of anatomic model building on medical students’ surgical skills23. From textbooks to headsets: the role of virtual reality in improving medical students’ understanding of liver anatomy24. The Symposium of Medical Student Leadership Development: an initiative to develop future surgical and health care leaders25. Effectiveness of near-peer teaching and experiential learning of casting and splinting: a medical student’s perspective26. Development of a novel simulation-based mastery learning course for extracorporeal membrane oxygenation (ECMO) cannulation27. Barriers to Black medical students and residents pursuing and completing surgical residency in Canada: a qualitative analysis28. Introduction of an academic half-day teaching for clinical clerks in surgery: a pilot study29. Efficiency of verbal intelligent tutor instruction in neurosurgical simulation: a randomized controlled trial30. Creation of a novel mindfulness-based cognitive therapy curriculum for surgical trainees: Mindfulness Integration in Surgical Training (MIST) 231. Comparison of ChatGPT and Gemini in responding to pediatric surgery clinical scenarios32. Examining the quality and quantity of verbal feedback in the operating room: a multispecialty study33. Influence of pig eye suturing on medical students’ perception of ophthalmic surgery in community medicine34. The use of different peer feedback frequencies in the acquisition of surgical skills using a decentralized model of simulation

2025· review· en· W4407220134 on OpenAlexaffvenueabout
Daniel Josué Guerra Ordaz, Jessica Maher, Alexandra D’Souza, Ralf M. Bader, Nancy Posel, Emily Lan‐Vy Nguyen, Khaled Skaik, Cariane Driad, Jimmy Ng, Lucy Yang, Giancarlo Sticca, Gizelle Francis, Xin Yu Yang, Farbod Niazi, Joseph D. Petruccelli, Gregory Mikerov, Justine Colivas, Jason Kreutz, Sonaina Chopra, Emily Volfson, Denesh Peramakumar, Prachikumari Patel, Alicia Belaiche, Constance Bouthillier, Charlotte McEwen, Edgar Akuffo‐Addo, Bianca Giglio, Victoria Tran, Megan Skakum, Rachael Allen, Alyson McKenna, Magdalena Cordoba, Éolie Delisle, Rocío Brañes, Sophie Nguyen, Waiel Abdulaziz Daghistani, Maryam Mozafarinia, Carlos Cordoba, Marisa Dorling, Karen E.C. de Haan, Danah Fahad, Alexander Moise, Youssef Omar, Elysia Grose, Timothy J. Phillips, Shaishav Datta, Kyle R. Wanzel, Clementine Affana, Ashish Kumar, David Fleiszer, Ahmer Irfan, Jason Aubrey, Taylor M. Coe, Hala Muaddi, Roxana Bucur, Nadia Rukavina, Chaya Shwaartz, W S El-Masry, Devon Haseltine, Matthew Bilson, Mahmoud Moustafa, Maryam Wagner, Carlos Gomez‐Garibello, Xavier Sonesaksith-Turcotte, Émilie Sandman, Prévost Jantchou, Marie‐Lyne Nault, Ayesha Shakeel, Suffia Malik, Wiley Chung, Abdullah Al-Ani, Mohamed Bondok, Helen Chung, Patrick Gooi, Dominique Dorion, Yousef Abdelkhalek Saber Omar, Kalpesh Hathi, Timothy Philips, Lalenthra Naidoo, JEAN-FRANÇOIS TREMBLAY, Franck Vandenbroucke-Menu, Mai‐Kim Gervais, Julien Letendre, Hugues Jeanmart, Ariane Lacaille-Ranger, Abrar Ahmed, Zeel Patel, Saman Arfaie, Crystal Ma, Jack Legler, Emily Steinberg, Élie Fadel, Liam Murad, Julia Biris, Charles Desgagné, Brandon Noyon, Adam Dubrowski, Érica Patocskai, Donald F Mcphalen, Claire Temple‐Oberle, Jason M. Harley, Anita Acai, Amy Keuhl, Quang Ngo, Jonathan Sherbino, Ereny Bassilious, Elif Bilgiç, Zackary Tsang, Megan Mak, Mojgan Hodaie, Rebecca Hisey, Elizabeth H. Klosa, Farah Zaza, Gábor Fichtinger, Boris Zevin, James Lisondra, Albert Fung, Jacques Piché, Adam Hocini, Myriam Belaiche, Louise McNaughton-Filion, Tomas Cordoba, Iqbal Jaffer, Faizan Amin, Jeffrey H. Barsuk, William C. McGaghie, Matthew Sibbald, Jaycie Dalson, Kwame Agyei, Samiha Mohsen, Safia Yusuf, Clara Juandó‐Prats, Jory S. Simpson, Vanja Davidovic, Recai Yilmaz, Abdulmajeed Albeloushi, Mohamed Alhantoobi, Abicumaran Uthamacumaran, Ahmad Alhaj, Rothaina Saeedi, Trisha Tee, Rolando F. Del Maestro, Brenna Swift, Dana Soroka, Monica S. Pearl, Andrea N. Simpson, Elizabeth Miazga, Giuseppe Retrosi, Ingrid de Vries, Stephen Mann, Glenio B. Mizubuti, Péter Szász, Andrew Farah, Omar Toubar, Siddharth Nath, Stephanie Chan, Roxanne Morneau-Carrier, Roxane Macret, Sandy Abdo, Florence Pelletier, Melissa Kyriakos

Bibliographic record

VenueCanadian Journal of Surgery · 2025
Typereview
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of ManitobaSt. Michael's HospitalToronto General HospitalCanadian Medical AssociationUniversité de MontréalOntario Tech UniversityHealth Sciences CentreUniversity of CalgaryMcMaster UniversityQueen's UniversityCégep de l'OutaouaisOccupational Cancer Research CentreUniversity Health NetworkMcGill University Health CentreMcGill UniversityDalhousie UniversityUniversity of OttawaToronto Western HospitalUniversity of British ColumbiaTrillium Health CentreUniversité de SherbrookeWestern UniversityBell (Canada)University of TorontoCentre Hospitalier Universitaire Sainte-JustineCentre Hospitalier de l’Université de MontréalOntario Brain InstituteMcGill-Queen's University PressUniversity of SaskatchewanArtificial Intelligence in Medicine (Canada)Sunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRetrospective cohort studySurgeryBibliometricsGeneral surgeryLibrary science

Abstract

fetched live from OpenAlex

# 01. A 25-year retrospective of Canadian plastic surgery research and its influence: a thorough bibliometric study {#article-title-2} Bibliometric analysis is used to assess and interpret the academic output and impact within a specific field. We aimed to measure the quantity and quality of

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)0.015
metaresearch head score (Gemma)0.136
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.665

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.136
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0290.047
Science and technology studies0.0070.002
Scholarly communication0.0090.006
Open science0.0030.006
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0860.014

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 head0.508
GPT teacher head0.592
Teacher spread0.084 · 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.

Study designNot applicable
DomainMethods
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

Citations1
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Surgery→Same topicDiversity and Career in Medicine→French-language works237,207→