Using Classifications to Identify Pathological and Taphonomic Modifications on Ancient Bones: Do “Taphognomonic” Criteria Exist?
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.
Bibliographic record
Abstract
Pathological and taphonomic agents can sometimes produce bone modifications that seem indistinguishable from one another, even to an experienced eye. The aim of this study is to propose a classification system to identify modifications observed on skeletal elements from different environmental and chronological contexts, with similar morphologies but varied aetiologies. Two types of classifications, empirical and statistical, were constructed, tested by two independent observers and compared. This classification system aims to categorise, differentiate and identify pathological and taphonomic bone modifications. In this paper, we identify several taphonomic criteria and propose a new term, “taphognomonic”, to characterise criteria that are specific to particular taphonomic agents. The two classification methods complement each other by providing precise (empirical classification) and reliable (statistical classification) diagnostic criteria. Finally, criteria are highlighted to differentiate pseudo-pathological from pathological bone modifications, the ultimate goal being to reduce the risk of misdiagnosis.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it