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.
Bibliographic record
Abstract
The CONP Ethics and Data Governance Framework has been developed by the CONP Ethics and Governance Committee. This document is currently open for comment until August 17, 2019. For more information or to submit comments, please contact: adrian.thorogood@mcgill.ca Canadian Open Neuroscience Platform, Ethics and Governance Committee: Ann Cavoukian, Privacy by Design Centre of Excellence, Ryerson University John Clarkson, Ontario Brain Institute Jennifer Flynn, Division of Community Health and Humanities, Faculty of Medicine, Memorial University Richard Gold, Faculty of Law, McGill University Judy Illes, CM, PHD Division of Neurology, Department of Medicine, University of British Columbia. Bartha Knoppers, Centre of Genomics and Policy, McGill University (Chair) Roland Nadler, Center for Health Law, Policy & Ethics, University of Ottawa Walter Stewart, Walter Stewart and Associates Adrian Thorogood, Centre of Genomics and Policy, McGill University (Manager) The Ethics and Governance Committee would also like to acknowledge the numerous members of the CONP and scientific community who have contributed to this policy. <strong>Executive Summary</strong> This Framework outlines core ethical elements, general principles, and practical guidance for the neuroscience community in Canada and internationally, as it adopts open science practices and develops supporting information and communication technology (ICT) infrastructure, namely the Canadian Open Neuroscience Platform (CONP). Open science involves the rapid and wide distribution of scientific knowledge, in order to improve scientific collaboration, integrity, and reproducibility; accelerate discovery; and improve human health. If conducted responsibly, open science can foster the human right of everyone to share in scientific advancement and its benefits.<sup>1</sup> This Framework focuses on safeguarding the rights and interests of data subjects in open science contexts, which include autonomy, privacy, health, and inclusion. It should be interpreted with reference to the CONP mission.<sup>2</sup> <sup>1 </sup>United Nations, Universal Declaration of Human Rights (1948), art 27. <sup>2 </sup>Canadian Open Neuroscience Platform (CONP), “Our Mission” https://conp.ca/
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 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 | 0.004 | 0.006 |
| 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 | 0.009 | 0.016 |
| Open science | 0.008 | 0.017 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it