Journey to the Ice Age: discovering an ancient world
Bibliographic record
Abstract
At the end of the Ice Age, small groups of hunter-gatherers crossed from Siberia to Alaska and opened the last chapter in the human settlement of the earth. Many left little or no trace. But one group - the Early Paleo-Indians - exploded suddenly on the archaeological record about 11,500 years ago and expanded rapidly throughout North America and, eventually, into South America. Why was this group so successful? To understand this, we need to know how they coped with change and different Ice Age environments. This book, by archaeologist and curator Peter Storck, focuses on the challenges faced by the Early Paleo-Indians of northeastern North America. A revealing, autobiographical account, Journey to the Ice Age is at once a captivating record of Storck's archaeological discoveries, as well as an introduction to the practice, challenges, and spirit of archaeology. Whether you're in your teens or in your 80s, if you've ever wanted to roll back the present and see the landscape of the past, this book is sure to delight you. Designed to take readers on their own journey to the ice age, the book includes a guided tour through Southern Ontario's archaeology-rich landscape. Of interest to both professional and amateur, student and teacher, specialist and novice, this personal, often evocative, account is bound to satisfy anyone who's ever yearned to ask an archaeologist: How do you know where to dig? Why do you do what you do? Or what does it all mean? Peter Storck takes readers on an intellectual odyssey in this personal account of the archaeological discoveries that highlight his 30 year career.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.021 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".