CAD Extensions and Other Refinements to the LOCATE Workplace Layout Tool
Bibliographic record
Abstract
Abstract : The LOCATE workspace layout tool is a mature tool useful for practical design applications. It has been used to evaluate bridge configurations for a Tribal class (DDH280) destroyer of the Canadian Forces, to analyse proposed ship designs for the US Navy as part of their Surface Combatant-21 (SC-21) project and is currently being considered as part of work at the Canadian Regional Operations Centre. Other potential application areas include office and manufacturing plant layouts, command posts, aircraft cockpits and even computer screens. The work for this contract comprised refinements to the LOCATE workspace layout tool. A key concern was extending LOCATEs ability to deal With files created in other CAD packages and with creating similar output files for use in those same packages. A second important goal was to expand and refine select features of LOCATE. One feature of particular interest was the extension of overview summaries of link and obstruction functions and priority weights so that users will be able to examine, compare and edit those data in a convenient form. Finally, specifications for C + + data structures, such as those for goals, plans and models, were used in a continuing effort to build the kind of infrastructure needed to support a truly intelligent LOCATE.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".