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Record W3014801215 · doi:10.1016/j.arthro.2020.01.040

<i>Editorial Commentary:</i> Magnetic Resonance Imaging Evaluation of the Anterolateral Complex—Is Seeing Really Believing?

2020· editorial· en· W3014801215 on OpenAlexaff
Ian Al’Khafaji, Brian M. Devitt

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2020
Typeeditorial
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsRichmond Hospital
Fundersnot available
KeywordsAnterolateral ligamentMagnetic resonance imagingMedicineAnterior Cruciate Ligament InjuriesAnterior cruciate ligamentClinical PracticeMedical physicsRadiologyPsychologyAnterior cruciate ligament reconstructionPhysical therapy

Abstract

fetched live from OpenAlex

The anatomic and biomechanical role of the anterolateral complex (ALC) of the knee has gained increased interest in recent years. Specifically, a keen focus has been on magnetic resonance imaging (MRI) evaluation of the ALC in the setting of anterior cruciate ligament injury. Although many of these studies are well designed and conducted, they are based on a foundation of controversial gross anatomy and MRI protocols and scanners not typically used in standard practice. Ultimately, there is a lack of correlation between MRI evidence of injury to the ALC and clinical evaluation of anterolateral rotatory laxity. So, do we believe in what we see or believe in what we feel?

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)0.006
metaresearch head score (Gemma)0.035
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.030
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.035
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0030.001
Science and technology studies0.0040.004
Scholarly communication0.0060.006
Open science0.0050.001
Research integrity0.0300.028
Insufficient payload (model declined to judge)0.0090.010

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 head0.009
GPT teacher head0.274
Teacher spread0.264 · 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
GenreEditorial

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
Published2020
Admission routes1
Has abstractyes

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