The mummy of Shoshenq I re-discovered?
Bibliographic record
Abstract
In Gttinger Miszellen 198 (2004):55-62, R. L. Miller identifies a mummy formerly in the collection of the Niagara Falls Museum with that of Shoshenq I (though other candidates are not ruled out), primarily on the basis of a tree-ring calibrated radiocarbon date.A reexamination of the historical evidence cited by Miller in support for this contention makes such an identification implausible.Recently, R. L. Miller (2004) has proposed that the probable royal mummy formerly in the collection of the Niagara Falls Museum,1 Ontario, Canada, may be that of king Shoshenq I, the Libyan founder of Dynasty XXII.As part of a series of examinations undertaken by Miller, samples of tissue-abdominal skin and muscle (Miller 2004, 61)-were submitted for 14C AMS testing in 1994.This yielded an uncalibrated determination of 2734 60 BP, which can be calibrated with a probability of 95.4% to the period 1010-790 BCE using the OxCal 3.8 calibration (Miller 2004, 55, 57).Miller (2004, 56-58) argues that low peaks on the calibration graph would not rule out proposals to identify the mummy with one of the sons of Ramesses II, or with one of the Ramesside kings of Dynasty XX (Miller 2004, 58, citing personal communications with S. Orel, 1994 and 2001; see also Rose 2003, 23).It would, however, exclude earlier New Kingdom dates, and thus making the widely repeated claim that this is the mummy of Ramesses I particularly unlikely.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".