Bibliographic record
Abstract
CodaFebruary 2013.Houses tell a lot about the people who live in them.They are a canvas upon which past lives, stories, and memories find a way into the present.They tell of someone's aspirations and fears, of one's loves and dreams.Such were my thoughts as I walked into the house of Brigadier Khan, in a quiet residential area in the outskirts of Islamabad.The walls were covered with a number of family photographs.I saw the young brigadier on the day of his marriage -"many years ago," as he pointed out.Other pictures were showing his four daughters with their respective husbands and children, and one large image showed the whole family together.All of the brigadier's daughters were living in different places now: Vancouver, Manchester, Karachi.The fourth one, I can't recall.As the Brigadier pointed out, proudly, "it all started from me, and now they are all over the world with their families".In February 2013, at the time I interviewed him in his house in Islamabad, Brigadier Khan was 82 years old.Tall and skinny, his long fingers moved quickly as he generously talked to me about his life for over two hours, while sipping sweet chai and eating cookies and dry fruit.He enjoyed his time in the army -and he certainly enjoyed recalling the old days.The reason I was interviewing Brigadier Khan was because he had been responsible of the construction of "over 400 miles" of the KKH, in the 1960s and 1970s, when he was a commander of the Corps of Engineers of the Pakistani army.I had come to know Brigadier Khan through another prominent member of the Corps of Engineers, Brigadier (retired) Mumtaz Khalid.Brigadier Khalid was the author of a two-volume history of the construction of the KKH (2006; 2009), which I had carefully read and discussed with him over meetings at his house in Rawalpindi.Yet when my questions lingered around the relationships between Pakistani engineers and their Chinese counterparts, he suggested I get in touch with Brigadier Khan.He, Mumtaz Khalid told me, was working closely with the Chinese, and travelled extensively to Xinjiang and Beijing to discuss cooperations and protocols with Chinese officers.He had even met Zhou Enlai once, I was told.Brigadier Khan, as I arrived at his house, invited me to sit in a large living room, surrounded by sofa, with a big window pointing toward the small garden beside the street.As I walked in, I couldn't avoid noticing the huge carpet that was covering most of the room's space, a beautiful
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.785 | 0.652 |
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".