Bibliographic record
Abstract
Scalable distributed systems face inherent trade-offs arising from the relatively high cost of exchanging information between computing nodes. Brewer's CAP (Consistency, Availability, Partition-Tolerance) principle states that when communication becomes impossible between isolated parts of the system (i.e., the network is partitioned), then the system must give up either safety (i.e., sometimes return an incorrect result) or liveness (i.e., sometimes fail to produce a result). Abadi generalized Brewer's principle by defining the PACELC (if Partition then Availability or Consistency, Else Latency or Consistency) formulation, which captures the ob- servation that the trade-off between safety and liveness is often made in practice even while the network is reliable. Building on Gilbert and Lynch's formal proof of the CAP principle, this paper presents a formal treatment of Abadi's formulation and connects this result to a body of prior work on latency bounds for distributed objects.
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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 | 0.011 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.018 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".