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CJN volume 49 issue 5 Cover and Front matter
Andrea M. Kuczynski, Manav V. Vyas, Renato Puppi, X. Nguyen, Thomas Thanh, Jillian Jeerakathil, Mary-Lou Stang, Balraj Halabi, Brian E. Mann, Jeremy Buck, Mayank Rempel, Andrew Goyal, Shelley Demchuk, Tracy Valaire, Michael Wasylak, Everardo García-Estrada, Alberto Morales-Gómez, Azalea Garza-Báez, Arturo Sotomayor-González, Isaac Jair Palacios-Ortíz, Mariana Mercado-Flores, Angel Raymundo, Martínez-Ponce De León, Jose Danilo, Bengzon Diestro, Carmen Parra-Fariñas, Michael Balas, Zsolt Zádor, Noora Almusalam, Adam A. Dmytriw, Phavalan Rajendram, Rebecca Phillips, Abdullah Alqabbani, Emmad Qazi, Yangmei Li, Walter Montanera, Dipanka Sarma, Thomas R. Marotta, Aditya Bharatha, Julian Spears, Seyyed-Saleh Hashemi, Reza Hajati, Atefeh Davarzani, Mohammad Rohani, Fardad DanaeeFard, Mohammad Masoud, Rahimi Bidgoli, Farzad Fatehi, Ariana Kariminejad, Hossein Najmabadi, Shahriar Nafissi, Afagh Alavi, Simin Rahman, Ummatul Siddique, Supriyo Choudhury, Nazrul Islam, Akash Roy, Purba Basu, Shankar Anand, Mohammad Saharul Islam, Mohammad Shahi, Abu Nayeem, Tauhidul Islam Chowdhury, Mohammad Monir Shah, Jahirul Chowdhury, John‐Paul Taylor, Mark Baker, Stuart Baker, Hrishikesh Kumar, Amitabh Bhattacharya, Nitish Kamble, Ravi Yadav, Albert Stezin, Kumar Pal, Jimmy Li, Hinnoutondji Toffa, Khoa Dang, J. Alexander Viau, Dilan Patel, Wei Cheng, Miguel Cortel-LeBlanc, Avik Nath, Jeffrey J. Perry, Kristina Joyal, Jessica V. MacGregor, Lamia Hayawi, Richard Webster, Hugh J. McMillan, Neuroimaging Highlights, Vasileios Xydis, Anastasia Giantsouli, Effrosyni Styliara, George Α. Alexiou, Iliada Nakou, Loukas G. Astrakas, Maria I. Argyropoulou, Maria João Malaquias, Eduarda Pinto, Jorge Oliveira, João Parente Freixo, Carla Caseiro, Marina Magalhães, Patricia López Gómez, David Mato Mañas, Marta Drake-Pérez, Carlos Santos Jimenez, Esteban Garcia, Rubén Martín-Laéz Brief, Sumanth Shivaram, Madhu Nagappa, Venkata Doniparthi, Jitender Seshagiri, Periyasamy Saini, Sruthilakshmi Govindaraj, Sankaran Sinha, A. Madhu Bindu, Ethan Waisberg, Caberry W. Yu, Irina Sverdlichenko, Jonathan A. Micieli, Vinodray Mitesh, Ajith Chandarana, Syam Cherian, Mary Krishnan, Udit Glenda, Erika Leck, Gwynedd E. Pickett, Cody Lo, Andrea Jones, Tychicus Chen, Gloria Mak, Marvin Chum, Jian‐Qiang Lu, Robert Chen, Robert Hammond, Philippe Hout, Mahendranath Moharir, Tejas Sankar, Manas Sharma, Jeanne Teitelbaum, Richard Wennberg, Greg L. Bryan, Young London, Douglas W. Zochodne, James Sharpe, Robert Lee, Robert Ross, Mark A. MacLean, Jorge G. Burneo, Jodie Burton, Colin Chalk, K.C. Allen Chan, Alan Goodridge, Mark G. Hamilton, Michael D. Hill, Alan Jackson, Draga Jichici, Suneil K. Kalia, Daniel Keene, Julia Keith, Nir Lipsman, Stephen Lownie, Patrick McDonald, Joseph Megyesi, Tiago Mestre, Sarah A. Morrow, Michael Nicolle, Ian F. Parney, Narayan Prasad, Alex Rajput, Kesh Reddy, Larry Robinson, Ramesh Sahpaul, Jai Shankar, Madeleine Sharpe, Ashkan Shoamanesh, Sean Symons, Brian Toyota, Brian G. Weinshenker, Sam Wiebe, Jefferson R. Wilson, Amy Yu, Eugene Yu
Bibliographic record
VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFront coverFront (military)Cover (algebra)Volume (thermodynamics)Environmental scienceContent (measure theory)MathematicsGeographyPhysicsEngineeringMeteorologyMechanical engineeringThermodynamics
Abstract
OpenAlex records an abstract for this work, but it could not be fetched just now.
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.
metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.163
Threshold uncertainty score0.232
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.837 | 0.699 |
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.
Opus teacher head0.035
GPT teacher head0.211
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation status
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
Study designNot applicable
Domainnot available
GenreOther
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".
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Citations0
Published2022
Admission routes1
Has abstractyes