Automated Coastal Engineering System, Version 1.07
Bibliographic record
Abstract
This note discusses a microcomputer-based software package that contains reliable state-of-the-art solutions to various coastal engineering problems.BACKGROUND In 1986 the Coastal Engineering Research Center (CERC) recommended to the Office, Chief of Engineers that an Automated Coastal Engineering System (ACES) be developed to give Corps offices an interactive computer based design capability in the field of coastal engineering.The recommendation was in response to a charge by the Chief of Engineers, LTG E. R. Heiberg III, to the Coastal Engineering Research Board to provide improved design capabilities to Corps coastal specialists.CERC formed an internal technical committee to develop recommendations for implementing an automated design System.This committee obtained input from Corps field offices regarding the form and development procedures preferred for the system.The information was obtained primarily from six regional workshops conducted in July 1986 and attended by more than one hundred coastal specialists.Based on recommendations from the workshops, a Pilot Committee composed primarily of Corps District and Division coastal specialists was formed in September 1986 to guide development of the ACES.In addition an Automated Coastal Engineering Group was formed in February 1987 within CERC to implement its development.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.294 | 0.316 |
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".