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Record W3133371171 · doi:10.1080/21678421.2020.1840795

Preface: promoting research in PLS: current knowledge and future challenges

2020· editorial· en· W3133371171 on OpenAlexaff
Hiroshi Mitsumoto, Martin R. Turner, Senda Ajroud‐Driss, Patricia L. Andres, Jinsy Andrews, Estela Área-Gómez, Juan Marcos Solano, Suma Babu, Richard J. Barohn, Peter Bede, Michael Benatar, Sheena Chew, Robin Conwit, Philippe Corcia, Merit Cudkowicz, Frank Davis, Mamede de Carvalho, Vivian E. Drory, Lauren Elman, Pam Factor‐Litvak, J. Americo Fernandes, Dominic Ferrey, Eoin Finegan, John K. Fink, Mary Kay Floeter, Christina Fournier, Angela Genge, Raghav Govindarajan, Volkan Granit, Georg Haase, Orla Hardiman, Matthew B. Harms, Ghazala Hayat, Terry Heiman‐Patterson, Bryan Alan Hill, Annemarie Hübers, Edward D. Huey, Omar Jawdat, Osamu Kano, Kristen Kau, Matthew C. Kiernan, Yasushi Kisanuki, Jerome E. Kurent, Justin Kwan, Dale J. Lange, Albert C. Ludolph, Ian R. Mackenzie, Giovanni Manfredi, David Marren, Mitsuya Morita, Jennifer Murphy, Sharon Nations, Björn Oskarsson, Sabrina Paganoni, David Pellerin, John Ravits, Kourosh Rezania, Guy A. Rouleau, Stephen N. Scelsa, Teepu Siddique, Nailah Siddique, Vincenzo Silani, Zachary Simmons, Jeffrey Statland, Bryan J. Traynor, Marka van Blitterswijk, Leonard van den Berg, David Walk, Deborah L. Warden, James Wymer

Bibliographic record

VenueAmyotrophic Lateral Sclerosis and Frontotemporal Degeneration · 2020
Typeeditorial
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersAgence Nationale de la RechercheMotor Neurone Disease Association
KeywordsAmyotrophic lateral sclerosisCurrent (fluid)Frontotemporal dementiaPsychologyKnowledge managementMedicineComputer scienceEngineeringPathologyDisease

Abstract

fetched live from OpenAlex

"Preface: promoting research in PLS: current knowledge and future challenges." Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 21(sup1), pp. 1–2

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.120
GPT teacher head0.364
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2020
Admission routes1
Has abstractyes

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