Bibliographic record
Abstract
ics of in cen tive con tractin g: n ote. Am erican Econ om ic Review , 65, 478-483. Chapm an , C.B. (1979) Large en gin eerin g project risk an alysis. IEEE Tran saction s on En gin eerin g Man agem en t, EM-26, 78-86. Chapm an , C.B. (1988) Scien ce, en gin eerin g an d econ om ics: OR at th e in terface. Jou rn al of the Operation al Research Society, 39(1), 1-6. Chapm an , C.B. (1990) A risk en gin eerin g approach to project m an agem en t. In tern ation al Jou rn al of Project Man agem en t, 8(1), 5-16. Chapm an , C.B. (1992a). Risk Man agem en t: Predictin g an d Dealin g w ith an U n certain Fu tu re. Exh ibit # 748, Provin ce of On tario En viron m en tal Assessm en t Board H earin gs on On tario H ydro's D em an d/ Supply Plan , subm itted by the In depen den t Power Producers Society of On tario, 30 Septem ber. Chapm an , C.B. (1992b). My two cen ts worth on h ow OR sh ould develop. Jou rn al of the Operation al Research Society, 43(7), 647-664. Chapm an , C.B. (2006) Key poin ts of con ten tion in fram in g assum ption s for risk an d un certain ty m anagem en t. In tern ation al Jou rn al of Project Man agem en t, 24, 303-313. Chapm an , C.B. (2008) Soun d, practical an d fair allowan ces for un certain ty: a startin g position for 'clarity m an agem en t', in Ton y: An In credible Man (Wan g, W., Sh arples, S. an d Martin , H. (eds)).
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.451 | 0.027 |
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".