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Record W2292848290 · doi:10.1302/0301-620x.91b2.21567

Medical negligence in orthopaedic surgery

2009· article· en· W2292848290 on OpenAlex
Sam Gidwani, S. M. R. Zaidi, M. Bircher

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2009
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsHand and Upper Limb Clinic
Fundersnot available
KeywordsPound (networking)PlaintiffMedicineExpert witnessMedical negligenceLawWitnessSettlement (finance)PaymentGeneral surgerySurgeryPolitical scienceBusinessFinance

Abstract

fetched live from OpenAlex

Payments by the NHS Litigation Authority continue to rise each year, and reflect an increase in successful claims for negligence against NHS Trusts. Information about the reasons for which Trusts are sued in the field of trauma and orthopaedic surgery is scarce. We analysed 130 consecutive cases of alleged clinical negligence in which the senior author had been requested to act as an expert witness between 2004 and 2006, and received information on the outcome of 97 concluded cases from the relevant solicitors. None of the 97 cases proceeded to a court hearing. Overall, 55% of cases were abandoned by the claimants' solicitors, and the remaining 45% were settled out of court. The cases were settled for sums ranging from pound 4500 to pound 2.7 million, the median settlement being pound 45,000. The cases that were settled out of court were usually the result of delay in treatment or diagnosis, or because of substandard surgical technique.

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.

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)0.012
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.354
Teacher spread0.305 · 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