Data Supplement for the IGSC 2019 paper ``A benchmark suite for control algorithms of retractable wind-energy harvesters''
Bibliographic record
Abstract
The following files comprise the Data Supplement to which the IGSC 2019* paper ``A benchmark suite for control algorithms of retractable wind-energy harvesters'' refers:1) "training_and_testing_wind_data_for_all_30_stations.zip" - Thirty training and testing files, each with approximately nine and two years, respectively, of minute-by-minute windspeeds and simulated predicted day-ahead windspeeds;License: Open Data Commons Attribution License: http://opendatacommons.org/licenses/by/1.0 2) "HOEP(Hourly Ontario Energy Price)_2004-2014(CADperKWH).zip" - An eleven-year hourly electricity price file;License: Attribution-NoDerivs 2.5 Generic (CC BY-ND 2.5): https://creativecommons.org/licenses/by-nd/2.5/Attribution: Copyright © 2017 Independent Electricity System Operator, all rights reserved. This information is subject to the general terms of use set out in the IESO's website (www.ieso.ca).3) "fuzzy_set_membership_functions_for_all_30_stations.zip" - A fuzzy-set-membership-function file describing membership in the set NOT WINDY AT for each of the 30 weather stations;License: Open Data Commons Attribution License: http://opendatacommons.org/licenses/by/1.04) "STL_Sunset_Times.csv" - A file containing sunset times for the city of St. Louis, Missouri, for all days in the years 2004-2014, inclusive, which are used in the definition of quiet hours for St. Louis;License: Open Data Commons Attribution License: http://opendatacommons.org/licenses/by/1.05) "Noise_Allowed_Time_Definitions_All_Stations.csv" - A file delineating when noise is allowed for municipalities corresponding to the 30 weather stations;License: Open Data Commons Attribution License: http://opendatacommons.org/licenses/by/1.0 6) "Survata_F5962F2D_guy_p_gadola_iii.xlsx" - A spreadsheet containing survey results of preferences toward retractable wind-energy harvesters;License: Open Data Commons Attribution License: http://opendatacommons.org/licenses/by/1.0*The Tenth International Green and Sustainable Computing Conference
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 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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.272 | 0.123 |
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".