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Record W3127457110 · doi:10.1145/3197406.3197420

Proving PACELC

2018· article· en· W3127457110 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACM SIGACT News · 2018
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsLivenessComputer scienceScalabilityConsistency (knowledge bases)Partition (number theory)Cache coherenceLatency (audio)Model checkingTheoretical computer scienceDistributed computingComputer networkMathematicsArtificial intelligenceOperating systemCombinatoricsTelecommunications

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.840
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.019
GPT teacher head0.264
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it