Bibliographic record
Abstract
This article explores Metalwork Wear Analysis (MWA) onspearheads dating to the Early Bronze Age (c. 1700–1100BCE), utilizing drawing-based investigation as an alternative to methodological accepted methods of microscopical examination. The study compares the results from drawingbased analysis with earlier microscopic studies, notably Horn’s (2013) research. The findings suggest that Nordic Bronze Age spearheads were multifunctional weapons used for both thrusting and slashing, challenging the traditional view of spears as solely thrusting implements. The methodological approach emphasizes the potential of lowcost, scalable, illustration-based MWA, while acknowledging limitations such as subjectivity, corrosion and the lack of three-dimensional perspectives. The article advocates for systematic integration of drawings and object analysis, proposing that broader adaptation of the methodological framework could deepen insights into Bronze Age warfare and weapon usage. Overall, it underscores the importance of re-examining weapon functions through innovative, collaborative research techniques, offering new avenues for understanding prehistoric conflict and spearmanship.
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 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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.018 | 0.024 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.025 | 0.013 |
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".