Development of a Dry Bone MDCT Scanning Protocol for Archaeological Crania
Bibliographic record
Abstract
This poster discusses the development of a multi-detector computed tomography (MDCT) scanning protocol for dry bone skulls, using a Toshiba Aquilion 64-slice scanner at Quinnipiac University, in North Haven, Connecticut. Unfortunately, for individuals working in paleoimaging, the preset image manipulation factors have been developed for hydrated living tissues. Three likely preset protocols were selected as the initial starting place for the dry bone study in preparation for a potential large sample scanning session of skulls from Peabody Museum of Natural History at Yale University. Each protocol had specific raw data acquisition parameters and algorithm, mathematical manipulations of the raw data, intended to produce a particular effect on the resulting displayed images such as edge enhancement or beam hardening correction. The effects of these subtle data manipulations will be discussed and demonstrated. Finally, although the protocol was developed on a Toshiba unit, the manipulation factors presented can be employed as, at least a starting point for the optimization of image quality while reducing the magnitude of data collected from the scanners of other manufacturers.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".