Bibliographic record
Abstract
We will situate the concept of an avatar (a working simulacrum of part of a system separated from it in space or time) with respect to traditional concepts of programming language and systems design. Whilst much theory and practice argues in favour of insulation (the creation of architectural boundaries prohibiting the leakage of information) we will find that many successful systems take a diametrically opposed approach. We name this family of systems as those based on externalised state transfer. Rather than hiding implementation details behind APIs, object interfaces or similar, these systems actively advertise their internal structure and its coordinates via data and metadata. Examples of these systems include RESTful web applications, MIDI devices, and the DWARF debugging file format. We discuss such systems and how we can purposefully design new systems embodying such virtues in a more distilled form.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.010 | 0.027 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".