Parameter Value Language A Tutorial - CCSDS 641.0-G-2
Bibliographic record
Abstract
This Report describes the Parameter Value Language (PVL) and provides a description of how and why one would use this language for information interchange.This document has been reconfirmed by the CCSDS management Council through March 2011.This document describes a keyword-value language, the Parameter Value Language (PVL); it provides a description of how and why one would use this language to interchange information. This document provides the rationale for the development of PVL, its intended usage, its format and construction rules as well as suggested practices and cautions. Most users will be able to use the language after reading this document. Those individuals who are responsible for implementing software associated with the language, or who need more detailed information should also consult the Parameter Value Language Specification (CCSD0006 and CCSD0008) (reference [[2]]) which contains the formal specification for the language. Both the basic version (CCSD0006) and the extended character set version (CCSD0008) of PVL are specified in that document; both versions are discussed in this document.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".