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Record W2071602539 · doi:10.1016/j.jot.2014.07.004

International Combined Orthopaedic Research Societies: A model for international collaboration to promote orthopaedic and musculoskeletal research

2014· article· en· W2071602539 on OpenAlexaff
Theodore Miclau, Nobuo Adachi, John Antoniou, Nicola Baldini, Gordon Blunn, Steven K. Boyd, Je‐Ken Chang, Bernd Grimm, Xia Guo, Gun‐Il Im, Feza Korkusuz, Oscar K. Lee, Andrew W. McCaskie, R. Geoff Richards, Gautam M. Shetty, Suresh Sivananthan, Tingting Tang, Jiake Xu, Ling Qin

Bibliographic record

VenueJournal of Orthopaedic Translation · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsAlberta Bone and Joint Health InstituteUniversity of CalgaryMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsEngineering ethicsMedicinePolitical sciencePublic relationsEngineering

Abstract

fetched live from OpenAlex

In October 2013, the International Combined Orthopaedic Research Societies (ICORS; http://i-cors.org) was founded with inaugural member organisations from the previous Combined Orthopaedic Research Society, which had sponsored combined meetings for more than 2 decades. The ICORS is dedicated to the stimulation of orthopaedic and musculoskeletal research in fields such as biomedical engineering, biology, chemistry, and veterinary and human clinical research. The ICORS seeks to facilitate communication with member organisations to enhance international research collaborations and to promote the development of new international orthopaedic and musculoskeletal research organisations. Through new categories of membership, the ICORS represents the broadest coalition of orthopaedic research organisations globally.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.420
Teacher spread0.346 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations3
Published2014
Admission routes1
Has abstractyes

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