Bibliographic record
Abstract
This readme.txt file was generated on 2021-02-06 by Mohsen Ghaffari and Dr. Mansoor Davoodi-Monfared. GENERAL INFORMATION Adjacency Matrix of Real-World (Nine cities) Principal Investigator Contact Information Mohsen Ghaffari Department of Computer Science and Information Technology, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran email: mohsen.ghaffari@iasbs.ac.ir Associate or Co-investigator Contact Information Dr. Mansoor Davoodi-Monfared Department of Computer Science and Information Technology, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran email: mdmonfared@iasbs.ac.ir Date of data collection 2020.04.29 The geographic location of data collection Sareyn, Ardabil, Iran Barcelona, Spain London, England Munich, German New York, U.S. Paris, France Tehran, Iran Toronto, Canada Zanjan, Iran SHARING/ACCESS INFORMATION Link to the publication that uses the data Shortest Path Problem on Uncertain Networks: An Efficient Two Phases Approach, Mansoor Davoodi & Mohsen Ghaffari, Computers, and Industrial Engineering, 2021. sources https://www.openstreetmap.org/ https://github.com/AndGem/OsmToRoadGraph Please cite Shortest Path Problem on Uncertain Networks: An Efficient Two Phases Approach, Mansoor Davoodi & Mohsen Ghaffari, Computers, and Industrial Engineering, 2021. DATA & FILE OVERVIEW Files List Note: Each node is a crossover between streets, and edges are direct paths between nodes. Each file contains at least one emergency state. Ardabil.csv The adjacency matrix of Saryen city, which is a small city in Ardabil. It includes 1892 nodes and 2088 edges. Barcelona.csv The adjacency matrix of a part of Barcelona city, which includes 1397 nodes and 1506 edges. London.csv The adjacency matrix of a part of London city, which includes 1176 nodes and 1225 edges. Munich.csv The adjacency matrix of a part of Munich city, which includes 1148 nodes and 807 edges. New York.csv The adjacency matrix of a part of New York City, which includes 1433 nodes and 1667 edges. Paris.csv The adjacency matrix of a part of Paris city, which includes 1417 nodes and 1575 edges. Tehran.csv The adjacency matrix of a part of Tehran city, which includes 1045 nodes and 1071 edges. Toronto.csv The adjacency matrix of a part of Toronto city, which includes 1162 nodes and 1227 edges. Zanjan.csv The adjacency matrix of a part of Zanjan city, which includes 1062 nodes and 1208 edges. METHODOLOGICAL INFORMATION We extract a part of road graphs of some cities using https://www.openstreetmap.org/ and the presented source code in https://github.com/AndGem/OsmToRoadGraph. Note that all the selected maps include at least one emergency center, such as a hospital or fire station. We define the weight of the connections as the travel time for the corresponding connection in the network.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".