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Record W2518948768 · doi:10.47671/tvg.67.13.2001002

Whiplash: medicolegale aspecten

2011· article· nl· W2518948768 on OpenAlexaboutno aff
G VYNCKE, VAN GERVEN K, R LYSENS, Eric Geusens, VAN WAMBEKE P

Bibliographic record

VenueTijdschrift voor Geneeskunde · 2011
Typearticle
Languagenl
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsWhiplashMedicineMedical emergencyPoison control

Abstract

fetched live from OpenAlex

Auteur(s): VYNCKE G, VAN GERVEN K, LYSENS R, GEUSENS E, VAN WAMBEKE P , | Samenvatting: Een aantal medicolegale aspecten rond whiplash komen aan bod. Vooreerst worden een aantal schalen besproken die kunnen gebruikt worden bij de evaluatie van (late) whiplash. Ook de indeling van de Quebec Task Force (1995) en de door de Neck Pain Task Force (2000-2010) toegepaste indeling zijn hierbij bruikbare hulpmiddelen. Een kant-en-klaarrecept om de gevolgen van whiplash te beoordelen, bestaat echter niet. Goede klinische praktijkvoering en

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)0.002
metaresearch head score (Gemma)0.022
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: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0240.006

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 head0.132
GPT teacher head0.382
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
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

Citations0
Published2011
Admission routes1
Has abstractyes

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