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Record W3088744208 · doi:10.1007/s11547-020-01288-7

Value of Canadian C-spine rule versus the NEXUS criteria in ruling out clinically important cervical spine injuries: derivation of modified Canadian C-spine rule

2020· article· en· W3088744208 on OpenAlexaboutno aff
Parisa Ghelichkhani, Kavous Shahsavarinia, Afshin Gharekhani, Ali Taghizadieh, Alireza Baratloo, Fattah Hama Rahim Fattah, Najmeh Abbasi, Mohammed Ibrahim Mohialdeen Gubari, Gholamreza Faridaalee, Hossein Dinpanah, Mir Saeed Yekaninejad, Alireza Esmaeili, Michael E. Jones, Shaghayegh Askarian‐Amiri, Mahmoud Yousefifard, Mostafa Hosseini

Bibliographic record

VenueLa radiologia medica · 2020
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsnot available
FundersIran National Science Foundation
KeywordsNexus (standard)MedicineCervical spineConfidence intervalEmergency departmentClinical prediction ruleSurgeryInternal medicinePsychiatryEngineering

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.009
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.706

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.075
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.003
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0050.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.040
GPT teacher head0.329
Teacher spread0.288 · 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 designObservational
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

Citations18
Published2020
Admission routes1
Has abstractno

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