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Record W2886700759 · doi:10.1017/cjn.2016.457

A Consult Is Just a Page Away: A Prospective Observational Study on the Impact of Jinxing on Call Karma in Neurosurgery

2017· article· en· W2886700759 on OpenAlexaffvenue
Holger Joswig, Lauren Zarnett, David A. Steven, Martin N. Stienen

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2017
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsObservational studyNeurosurgeryMedicineExtant taxonProspective cohort studySignificant differenceRating scaleKarmaFamily medicinePsychologyPsychiatrySurgeryInternal medicineHistory

Abstract

fetched live from OpenAlex

OBJECTIVE: Our aim was to assess the impact of jinxing on "call karma" in neurosurgery. METHODS: We conducted a prospective observational study on 15 residents on call for the neurosurgery service, recording the total number of admissions, consults, deaths encountered, surgeries performed, hours of sleep and subjective call rating on a numeric rating scale (NRS) of 0-10 in terms of general awfulness. RESULTS: Some 204 on-call nightshifts were analyzed, of which 61 (29.9%) were jinxed and 143 (70.1%) were nonjinxed. Jinxes seemed to occur in clusters. The baseline parameters (experience, type of call coverage and superstition level) of the study groups were well balanced. A trend toward more surgeries was observed during jinxed nights, where residents slept significantly less (mean 147.8±96.2 vs. 180.9±106.1 min, p=0.037) and rated their on-call experience worse on the NRS (4.4±2.2 vs. 3.5±2.0, p=0.011), while there was no significant difference in number of admissions, consults or deaths. CONCLUSIONS: The act of jinxing ought to be avoided in the neurosurgical setting, as it might be potentially harmful to resident call karma, irrespective of level of experience, resources and personal beliefs.

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 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)0.005
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.202
GPT teacher head0.400
Teacher spread0.198 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2017
Admission routes2
Has abstractyes

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