Amber in Archaeology, Curt W. Beck, Ilze B. Loze, and Joan M. Todd (eds.) (2003)
Bibliographic record
Abstract
to bead number 637 on page 79 indicates it is to be found in Fig. 8.0 but it is actually in Fig. 7.0.Additional errors of the same type occur on pages 82 and 83: bead number 688 is referred to Fig. 8.1 but the bead is to be found in Fig. 8.0.Likewise, number 690 is found in Fig. 8.7 not 8.8; 693 is in Fig. 8.0, not 8.8; and 689 is in Fig. 8. 7, rather than 8.8.This catalog goes far beyond enhancing the Timeline exhibit.It encompasses an enormous swath of time, placing beads and the technologies developed to make them in their cultural and historical context, a true tour de force.It is a "must-have" resource for anyone, professional or novice, who is interested in ancient beads.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.054 |
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".