On Improved Care of Black Bass During Live-Release Competitive Angling Events – Recent Innovations and Associated Research Needs
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
FisheriesVolume 45, Issue 4 p. 178-183 Policy and Issues On Improved Care of Black Bass During Live-Release Competitive Angling Events – Recent Innovations and Associated Research Needs Steven J. Cooke, Corresponding Author Steven J. Cooke steven.cooke@carleton.ca orcid.org/0000-0002-5407-0659 Carleton University, Department of Biology and Institute of Environmental and Interdisciplinary Science, Fish Ecology and Conservation Physiology Laboratory, 1125 Colonel By Drive, Ottawa, ON, Canada, K1S 5B6Search for more papers by this authorAlice E. I. Abrams, Alice E. I. Abrams Carleton University, Department of Biology and Institute of Environmental and Interdisciplinary Science, Fish Ecology and Conservation Physiology Laboratory, Ottawa, ON, CanadaSearch for more papers by this authorAaron J. Zolderdo, Aaron J. Zolderdo Carleton University, Department of Biology and Institute of Environmental and Interdisciplinary Science, Fish Ecology and Conservation Physiology Laboratory, Ottawa, ON, CanadaSearch for more papers by this authorCory D. Suski, Cory D. Suski Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, ILSearch for more papers by this author Steven J. Cooke, Corresponding Author Steven J. Cooke steven.cooke@carleton.ca orcid.org/0000-0002-5407-0659 Carleton University, Department of Biology and Institute of Environmental and Interdisciplinary Science, Fish Ecology and Conservation Physiology Laboratory, 1125 Colonel By Drive, Ottawa, ON, Canada, K1S 5B6Search for more papers by this authorAlice E. I. Abrams, Alice E. I. Abrams Carleton University, Department of Biology and Institute of Environmental and Interdisciplinary Science, Fish Ecology and Conservation Physiology Laboratory, Ottawa, ON, CanadaSearch for more papers by this authorAaron J. Zolderdo, Aaron J. Zolderdo Carleton University, Department of Biology and Institute of Environmental and Interdisciplinary Science, Fish Ecology and Conservation Physiology Laboratory, Ottawa, ON, CanadaSearch for more papers by this authorCory D. Suski, Cory D. Suski Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, ILSearch for more papers by this author First published: 30 November 2019 https://doi.org/10.1002/fsh.10393Citations: 7Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume45, Issue4April 2020Pages 178-183 RelatedInformation
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it