The accuracy and precision of body mass estimation in non‐avian dinosaurs
Bibliographic record
Abstract
Inferring the body mass of fossil taxa, such as non-avian dinosaurs, provides a powerful tool for interpreting physiological and ecological properties, as well as the ability to study these traits through deep time and within a macroevolutionary context. As a result, over the past 100 years a number of studies advanced methods for estimating mass in dinosaurs and other extinct taxa. These methods can be categorized into two major approaches: volumetric-density (VD) and extant-scaling (ES). The former receives the most attention in non-avian dinosaurs and advanced appreciably over the last century: from initial physical scale models to three-dimensional (3D) virtual techniques that utilize scanned data obtained from entire skeletons. The ES approach is most commonly applied to extinct members of crown clades but some equations are proposed and utilized in non-avian dinosaurs. Because both approaches share a common goal, they are often viewed in opposition to one another. However, current palaeobiological research problems are often approach specific and, therefore, the decision to utilize a VD or ES approach is largely question dependent. In general, biomechanical and physiological studies benefit from the full-body reconstruction provided through a VD approach, whereas large-scale evolutionary and ecological studies require the extensive data sets afforded by an ES approach. This study summarizes both approaches to body mass estimation in stem-group taxa, specifically non-avian dinosaurs, and provides a comparative quantitative framework to reciprocally illuminate and corroborate VD and ES approaches. The results indicate that mass estimates are largely consistent between approaches: 73% of VD reconstructions occur within the expected 95% prediction intervals of the ES relationship. However, almost three quarters of outliers occur below the lower 95% prediction interval, indicating that VD mass estimates are, on average, lower than would be expected given their stylopodial circumferences. Inconsistencies (high residual and per cent prediction deviation values) are recovered to a varying degree among all major dinosaurian clades along with an overall tendency for larger deviations between approaches among small-bodied taxa. Nonetheless, our results indicate a strong corroboration between recent iterations of the VD approach based on 3D specimen scans suggesting that our current understanding of size in dinosaurs, and hence its biological correlates, has improved over time. We advance that VD and ES approaches have fundamentally (metrically) different advantages and, hence, the comparative framework used and advocated here combines the accuracy afforded by ES with the precision provided by VD and permits the rapid identification of discrepancies with the potential to open new areas of discussion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".