Bibliographic record
Abstract
This chapter is written specifically for the team member. It explains how the team member can use the documentation that supports the product development process to understand and perform the required work. Program and functional directors should read this chapter to understand the details of the process. INTEGRATED PRODUCT TEAM MEMBER RESPONSIBILITIES The program and functional directors will give IPT members various assignments from the project plan, and this chapter will show a team member how the process documentation helps to complete them. Understanding how the project plan is organized is critical to allowing a team member to find and assimilate quickly what he or she needs to know and how to complete an assignment. PERFORMING A SPECIFIC TASK Performing a specific task means doing work that contributes to the development of the customer's product. The program director bases the assignment of these tasks on the program plan and his or her judgment of how resources should be allocated. Because the program plan is developed from the workplan templates, most assigned tasks are described in the process documentation. Completing a task involves ❍ Understanding what the task involves, howit fits into the process integration framework, and to which customer deliverable it contributes ❍ Understanding the individual work products that result from completing the task ❍ Gathering the materials necessary to complete the task ❍ Performing the task
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.162 | 0.193 |
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".