Survival probability of the ancestors of the indigenous people of Canada who migrated during the last glacial maximum
Bibliographic record
Abstract
The purpose of this study is to examine the survival probability of the ancestors of the indigenous people of Canada during their migration to the last glacial maximum. The ancestors of the Indigenous people of Canada are believed to have migrated during the Last Glacial Maximum under severe ice-age conditions. However, the possibility of their survival is unclear. Creating a mathematical model, the survival probability of Indigenous ancestors who migrated to Canada and the effects of different factors were studied. Using logistic regression analysis, we evaluated the effects of different factors, such as the mean female life expectancy, average childbirth interval, and marriage age, on their survival probability. The results suggested that a polygamous community was more likely to survive. The survival probability was maximized in the cases of monogamy/unintentional migration (0.60), polygamy/unintentional migration (0.87), and marriage age of 15 years/monogamy/unintentional migration (0.76). However, the survival probability was low for many possible combinations of the mean female life expectancy and the average childbirth interval. The low survival probability would demonstrate the levels of resourcefulness, bravery, and wisdom that the Indigenous ancestors possessed to survive. A problem was that the available data on mortality and fertility were not specific to the ancestors of the Indigenous people of Canada. In the future, the accuracy of the survival probability of the ancestors of the Indigenous people of Canada will improve once quantitative research data on the ancestors’ life expectancy and childbirth are available.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".