Odontoid process angulation range in a South African skeletal population sample: An osteological study
Ricardo Jonker; Glen J. Paton; Shahed Nalla · 2025 · Translational Research in Anatomy
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Background: This study investigated the angulation of the odontoid process in a South African skeletal population to establish normative vertical angulation in the sagittal plane and assess variations across population affinity groups, biological sexes, and age categories. The study also investigated standardizing techniques for measuring the angle of the odontoid process. Methods: A cross-sectional study was conducted on 200 cervical axis vertebrae from the Raymond A. Dart Collection. Angulation measurements were taken using digital photographs, ImageJ software and statistical analyses (one-w
Abstract by Ricardo Jonker; Glen J. Paton; Shahed Nalla, Translational Research in Anatomy (2025) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data
Negative / Null Result ReportMeteorological Causes of the Secular Variations in Observed Extreme Precipitation Events for the Conterminous United States
Negative / Null Result ReportThe Next Generation of Sepsis Clinical Trial Designs
Negative / Null Result ReportAnalysis of DNA Methylation in Young People: Limited Evidence for an Association Between Victimization Stress and Epigenetic Variation in Blood
Negative / Null Result ReportStudy preregistration: an early example and analysis.
Negative / Null Result ReportInsights Into LSTM Fully Convolutional Networks for Time Series Classification
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: DOAJ · DOI 10.1016/j.tria.2025.100388
