Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Episode 123 - Born during the Great Depression,Ken Leishmanwas a stylish, good looking guy with a Clark Gable moustache. A married father of 7, he was adventurous, smart, charismatic, creative and enterprising. He used his skill as a small aircraft pilot to earn cash first as a fly in mechanic on prairie farms, then as a king cookery salesman. Ken was also deeply in debt, his sales business was failing and he craved an even more lavish lifestyle. To get what he wanted Ken wasn't above stealing it, but often got caught going back for more. After flying all the way to Toronto to rob banks on two separate occasions Ken was dubbed the Flying Bandit after getting caught during his second failed bank robbery. After Ken's release, he had an even more elaborate heist in mind - making off with a few hundred pounds of gold bullion in what would be the greatest gold theft in Canadian history. Sources: [Bandit - A portrait of Ken Leishman by Wayne Tefs] [Lost: Unsolved Mysteries of Canadian Aviation by Shirlee Smith Matheson] [In the Mind of a Mountie - Google Play] [This Was Manitoba: Kenneth Leishman - The Flying Bandit (UPDATED)] [Ottawa Citizen - Ken Leishman - Google News Archive Search] [Newspapers.com search - Ken Leishman + Canada] [Ken Leishman: The Flying Bandit - video dailymotion] [Ken Leishman: The Flying Bandit - YouTube] [Court Briefing for 1966 trial of Ken Leishman et al, Winnipeg Gold Heist] [The Flying Bandit - Winnipeg Free Press] [Canada history: Mar.1, 1966: the Great Winnipeg Gold Heist RCI | English] [The Flying Bandit - Winnipeg Free Press] [The flying bank robber died hard | Macleans | DECEMBER 29, 1980] 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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.206 | 0.009 |
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 it