Bibliographic record
Abstract
action phase, of foresight 384 ad hoc classifications 361 ad hoc groups 50, 301, 364, 451 ad hoc surveys 368, 410 adaptability, organizational 252, 258 adaptive capabilities 248, 309 adhocracy 253 advanced technologies 45, 351, 359, 450 advanced technology surveys (Canada) 50, 123-4 Advisory Board (NESTI) 241 African Intergovernmental Committee on Science, Technology and Innovation Indicators 51 ageing population 249, 328, 398, 420, 452 aggregate measures, economic performance 232-5 Aghion, P. 306 Åkerblom, M. 73, 76-8 altruistic punishment 427 American Recovery and Reinvestment Act 2009 (US) 336, 337 analytical publications 224-5 Annual Economic and Fiscal Report (Japan) 207 Annual Report on the Japanese Economy (Japan) 198 Apps 452 Aristotle 428 arrival cities 10
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 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.712 | 0.669 |
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".