Bibliographic record
Abstract
there are numerous biographies, memoirs and autobiographies of senior Canadian oil and gas personalities and one or two more are published each year.They form part of the broader Canadian business literature that has recorded and preserved a plane of our common life that is as much a part of our lifeblood as politics.If, however, you are expecting just another corporate life story when you pick up this book, you will be disappointed.Arne Nielsen's memoir on his life of geological, corporate and personal discovery is not a conventional business biography.It contains no plea bargaining or selfjustification.This is not a hymn of self-praise.The Arne Nielsen in this book is the modest unassuming man who scores of Canadians know without knowing the full extent of his rich life and astonishing accomplishments.In a career of six decades, Arne mastered an impressive list of skills in geology, corporate management, corporate governance and politics, but he never learned to be self-serving.One of his final achievements in a long and fruitful life is to have learned to write a book.Drafting this manuscript by hand and in many hours of reflection and dictation, Arne achieved the degree of detachment and perspective necessary for the story of the man and his times to override the litany of bragging rights that another in his position might have produced.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.055 | 0.056 |
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".