Bibliographic record
Abstract
Syntax in Nuprl ::::::::::::::::::::::::::::::::::::::::::::: 23 Eli Barzilay, Stuart Allen DOVE: a Graphical Tool for the Analysis and Evaluation of Critical Systems :::::::::::::::::::::: 33 Tony Cant, Jim McCarthy, Brendan Mahony Formalising General Correctness ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 36 Jeremy E. Dawson Automatic Constraint Calculation using Lax Logic ::::::::::::::::::::::::::::::::::::::::::::: 48 Jeremy E. Dawson, Matt Fairtlough Automating Fraenkel-Mostowski Syntax :::::::::::::::::::::::::::::::::::::::::::::::::::::: 60 Murdoch J. Gabbay AFormal Correctness Proof of the SPIDER Diagnosis Protocol :::::::::::::::::::::::::::::::::: 71 Alfons Geser, Paul S. Miner Using HOL to Study Sugar 2.0 Semantics ::::::::::::::::::::::::::::::::::::::::::::::::::::: 87 Michael J. C. Gordon Extending DOVE with Product Automata :::::::::::::::::::::::::::::::::::::::::::::::::::: 101 Elsa L. Gunter, Yi Meng A Higher-Order System for Representing Metabolic Pathways ::::::::::::::::::::::::::::::::::: 112 Sara Kalvala Higher-Order Pattern Unification and Proof Irrelevance ::::::::::::::::::::::::::::::::::::::::: 121 Jason Reed AVerification of Rijndael in HOL :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 128 Konrad Slind The K Combinator as a Semantically TransparentTagging Mechanism:::::::::::::::::::::::::::: 139 Konrad Slind, Michael Norrish FCM 2002 Invited Talk Real Numbers in Real Applications ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 146 John Harrison v vi FCM 2002 Workshop Papers A PVS Service for MathWeb :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 147 A. A. Adams, A. Franke, J. Zimmer Formalizing Real Calculus in Coq :::::::::::::::::::::::::::::::::::...
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".