Bibliographic record
Abstract
Part I. Introduction, Background and Review: 1. An introduction to stone tool life history and technological organization William Andrefsky, Jr 2. Lithic reduction, its measurement, and implications: comments on the volume Michael J. Shott and Margaret C. Nelson Part II. Production, Reduction and Retouch: 3. Comparing and synthesizing unifacial stone tool reduction indices Metin I. Eren and Mary E. Prendergast 4. Exploring retouch on bifaces: unpacking production, resharpening, and hammer type Jennifer Wilson and William Andrefsky, Jr 5. The construction of morphological diversity: a study of Mousterian implement retouching at Combe Grenal Peter Hiscock and Chris Clarkson 6. Reduction and retouch as independent measures of intensity Brooke Blades 7. Perforation with stone tools and retouch intensity: a Neolithic case study Colin Patrick Quinn, William Andrefsky, Jr, Ian Kuijt and Bill Finlayson 8. Exploring the dart and arrow dilemma: retouch indices as functional determinants Cheryl Harper and William Andrefsky, Jr Part III. New Perspectives on Lithic Raw Material and Technology: 9. Projectile point provisioning strategies and human land use William Andrefsky, Jr 10. The role of lithic raw material availability and quality in determining tool kit size, tool function, and degree of retouch: a case study from Skink Rockshelter (46NI445), West Virginia Douglas H. MacDonald 11. Raw material and retouched flakes Andrew P. Bradbury, Philip J. Carr and D. Randall Cooper Part IV. Evolutionary Approaches to Lithic Technologies: 12. Lithic technological organization in an evolutionary framework: examples from North America's Pacific Northwest region Anna Marie Prentiss and David S. Clarke 13. Changing reduction intensity, settlement, and subsistence in Wardaman Country, Northern Australia Chris Clarkson 14. Lithic core reduction techniques: modeling expected diversity Nathan B. Goodale, Ian Kuijt, Shane J. Macfarlan, Curtis Osterhoudt and Bill Finlayson.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".