Bibliographic record
Abstract
Since their inception in the U.S. in the 1970s, automated people mover systems have become numerous, with installations around the world. Because APMs are inherently complex systems that involve multiple interacting subsystems, new technology and public safety, it is essential to establish minimum standards for their design, construction, operation and maintenance. The paper describes the benefits of standardization to organizations that specify and procure APM systems, regulatory authorities, system suppliers, system operators, system users and the general public. The consensus approach to standard writing is described and evaluated in terms of fairness, objectivity and effectiveness. Balance in APM Standards Committee membership and openness and transparency of the standards creation process are evaluated. The scope of the APM standard and potential overlap with other related standards produced within other standards-developing organizations is discussed. The degree to which a standard can gain worldwide acceptance, having been developed by an American organization with global membership, is also considered.
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 | 0.060 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".