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Record W7113520373

Wise wizards words of wizdom:ISBS 2018 Auckland wizen wizards keynote panel

2018· article· en· W7113520373 on OpenAlexaboutno aff

Bibliographic record

VenueUWA Profiles and Research Repository (UWA) · 2018
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsnot available
Fundersnot available
KeywordsPanel discussionWonderGermanSession (web analytics)
DOInot available

Abstract

fetched live from OpenAlex

In keeping with our Kiwiana theme, we will have a Wise Wizards Panel (yes, think Lord of the Rings movie) to answer interactive questioning from the delegates. Panel members are prestigious previous Geoffrey Dyson awardees, Life members, and ISBS Fellows: Professors Patria Hume, Bruce Elliott, Joe Hamill, Walter Herzog and Juris Terauds. Professor Walter Herzog is a Professor at the University of Calgary. Professor Joe Hamill is currently President of the International Society of Biomechanics. Professor Patria Hume was the inaugural SPRINZ Director at the Auckland University of Technology. Professor Juris Terauds and Professor Bruce Elliott are both Emeritus Professors. Professor Bruce Elliott’s philosophy has always been “a good question leads to beneficial research”. Come prepared to ask these wise biomechanists all the things you have ever wanted to know about biomechanics, as a discipline and a career. Via the session chairs Associate Professor Jacqueline Alderson and Professor Gareth Irwin, and using a dedicated feed arranged by our ISBS Social Media Coordinator Kylie Robinson, you will be able to ask questions like; · What does it take to have a successful academic career as a biomechanist? · Where are some of the best experiences that can be gained in applied biomechanics? · What is your crystal ball prediction of what biomechanics specialists will focus on in 10 years time? We hope that delegates, especially student and early career researchers, take up this unique opportunity to gather insight from those in whose footsteps they walk. Maybe the paths that you each shall tread are already laid before your feet, though you do not see them. - Lady Galadriel

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.515
Threshold uncertainty score0.692

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0110.004
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.5150.284

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 head0.038
GPT teacher head0.296
Teacher spread0.258 · 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
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
Published2018
Admission routes1
Has abstractyes

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