The Mystery of The Mad Trapper of Rat River (NT)
Bibliographic record
Abstract
Episode 103 - In this episode we're heading to the Inuvik area of the Northwest Territories, near Fort McPherson. Along the Rat River in the summer of 1931 a stranger was first seen by two indigenous men canoeing on the river. He was a stranger who, save for a short visit to town for supplies, kept to himself. The man was later accused of interfering with the traps of other hunters and trapping without a license. When RCMP went to investigate hell broke loose, culminating in attempted murder of one RCMP constable and the murder of another at the hands of the man. The man, known by the alias Albert Johnson, lead RCMP on a six week chase across the frozen tundra before he was taken down. His true identity remains a mystery. Come see us at CrimeCon in Orlando from May 1-3, 2020. Use POUTINE2020when buying your tickets. Sources: [The Hunt For The Mad Trapper Myth Merchant Films] [The Mad Trapper of Rat River by Nash Neary] [Goodreads.com - The Mad Trapper of Rat River by Dick North] [Who was the Mad Trapper of Rat River? | Macleans | OCTOBER 1 1955] [Goodreads.com - The Mad Trapper: Unearthing a Mystery by Barbara Smith] [NWT and Y History project - may.htm] [The RCMP Hunt for the Mad Trapper The Wop May Chronicles] [Constable Millens Cairn PWNHC | CPSPG] [CBC - Mad Trapper not a Canadian, scientific tests discover] [GlobalTV - Northern Mysteries- The Mad Trapper Albert Johnson] [Albert Johnson, The Mad Trapper of Rat River | The Canadian Encyclopedia] [Mackenzie River] [The RCMP Hunt for the Mad Trapper The Wop May Chronicles] Support the show: https://www.patreon.com/darkpoutine See omnystudio.com/policies/listener for privacy information.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.047 | 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; both teacher heads agree on what is shown here.
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".