SIMS oxygen isotope analysis of human dental tissues from Fidler Mounds (EaLf-3), MB : mobility during Manitoba's Middle and Late Woodland periods
Bibliographic record
Abstract
Secondary ion mass spectrometry (SIMS) was used to obtain stable oxygen isotope data from the dental tissues of 12 individuals once interred at Fidler Mounds (EaLf-3), a cemetery mound site located in south-central Manitoba, 79 kilometers north of Winnipeg.Fidler Mounds was originally constructed c. i 8008P and was utilized as a burial ground by precontact peoples in Manitoba for approximately 1000 years thereafter.The use of SIMS allowed the researcher to obtain several in situ ôl80 values from each individual's intact cementum, dentin and enamel.These values show that rnobility patterns during Manitoba's middle and late Woodland period were extremely complex and varied.Additionally, intra-tissue ôl80 variability recorded through SIMS analysis indicates that traditional mass spectrometry may not be appropriate for assessing migration patterns within highly mobile populations.(Anthony, 1990; Trigger, 2006).This was especially the case in North American Processual archaeology (Anthony, 1 990).This is not to say that Culture History was completely purged from archaeological discourse after the 1940's.Many of its major theoretical tenets, such as the importance of geographically and temporally contextualizing material culture, survive in current theory.The Culture Historical paradigm itself continued to be applied in one form or another at the fringes of academia for much of the twentieth century (Syms, 1978).In Manitoba, where theoretical debate chronically lags twenty years behind dominant discourse, papers and books describing and debating the composition, geographical limits and temporal boundaries of past cultures within the province and surrounding areas make
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".