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Record W4213285444 · doi:10.1002/crq.21280

Issue Information

2021· paratext· en· W4213285444 on OpenAlexaff
Debarun Chakraborty, Wendrila Biswas, Ganesh Dash, Michael Kern, L Steven Smutko, Mykola Lohvinenko, M.V. Starynskyi, Л Л Руденко, Iryna Kordunian, Rachael Field, Jonathan Crowe, Dorcas Quek, Anderson Helena, Desivilya Syna, Mohammed Abu‐Nimer, Lin Adrian, Susan Allen, Kennedy Amone-P'olak, Daniella Arieli, Dale Bagshaw, Michał Bilewicz, Lisa Blomgren Amsler, Rita Callahan, Lorig Charkoudian, Mediation Community, Peter C Arnold, Melissa Conley, Geoffrey Corry, Esra Çerağ, Kirk Emerson, Ronald Aylmer Fisher, Victor J. Friedman, Howard Gadlin, Alan Gross, Amanda Guidero, Landon E. Hancock, Toran Hansen, Tim Hedeen, Tricia S. Jones, Marnie Jull, Israel J. Katz, Sanda Kaufman, Kenneth Kressel, Ran Kuttner, Richard McGuigan, Cécile Mouly, Étienne Mullet, Inbal Koriat, Cheryl A. Picard, Brian Polkinghorn, Kerri Quinn, Rachel Rafferty, Raye Rawls, Colin Rule, Medical Director, Donald T. Saposnek, Terry Savage, Tyler A. Scott, Helen Shurven, Med Llb, Aldís G. Sigurðardóttir, Baissou Sissoko, Barbara Tint, A Turk, Maria R. Volpe, Gregg B. Walker, Sarah Wallis, William C. Warters, Nancy A. Welsh, Celeste P.M. Wilderom, Leah Wing

Bibliographic record

VenueConflict Resolution Quarterly · 2021
Typeparatext
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsCarleton UniversityRoyal Roads University
Fundersnot available
KeywordsCitationComputer scienceInformation retrievalWorld Wide Web

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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)0.002
metaresearch head score (Gemma)0.011
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 score0.086
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.006
Science and technology studies0.0020.001
Scholarly communication0.0080.004
Open science0.0020.003
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.9140.865

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 head0.022
GPT teacher head0.347
Teacher spread0.325 · 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; 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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractno

Explore more

Same venueConflict Resolution QuarterlySame topicCross-Border Cooperation and IntegrationFrench-language works237,207