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Record W3147815094 · doi:10.1016/j.arthro.2021.01.030

Regarding “Arthroscopic Bankart Repair With and Without Curettage of the Glenoid Edge: A Prospective, Randomized, Controlled Study”

2021· letter· en· W3147815094 on OpenAlexaff
Aaron Gazendam, Moin Khan

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2021
Typeletter
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineRandomized controlled trialArthroscopySurgeryCurettageOrthopedic surgery

Abstract

fetched live from OpenAlex

With great interest, we read Desai et al.’s recent study, titled “Arthroscopic Bankart Repair With and Without Curettage of the Glenoid Edge: A Prospective, Randomized, Controlled Study.”1 The authors reported that arthroscopic Bankart repair with curettage of the glenoid edge significantly reduced the incidence of recurrence of instability postoperatively when compared with repair without curettage. We commend the authors for conducting and publishing a randomized controlled trial (RCT) with long-term follow-up.

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)0.060
metaresearch head score (Gemma)0.168
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: Commentary · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.168
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.010
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0110.006
Insufficient payload (model declined to judge)0.0090.001

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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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
GenreCommentary

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

Citations2
Published2021
Admission routes1
Has abstractyes

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