Procedures for Emergency Logistic Assistance
Bibliographic record
Abstract
This manual provides guidance to health service support (HSS) planners at all echelons of care within a theater of operations (TO). It contains a digest of the accepted principles and procedures pertaining to HSS planning. Information in this publication is applicable across the spectrum of military operations. It is compatible with the Army’s combat service support (CSS) doctrine. Readers should have a fundamental understanding of Field Manuals (FMs) 8-10, 100-5, 100-10,100-15, 100-20, 101-5, and 101-10-1/1 and-1/2. The planner must supplement or replace the data in this manual with any known factors to meet the needs of his particular situation. The staffing and organizational structure presented in this publication reflect information in the most current living tables of organization and equipment (LTOE) as of calendar year 1992. However, staffing is subject to change to comply with manpower requirements criteria outlined in Army Regulation (AR) 570-2. Your table of organization and equipment (TOE) can be subsequently modified. A series of FMs currently under development will provide techniques and procedures for specific HSS organizations and activities in the TO. These manuals will be published over the next several years. This publication implements the following North Atlantic Treaty Organization (NATO) and American, British, Canadian, and Australian (ABCA) International and Quadripartite Standardization Agreements
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.511 | 0.495 |
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".