MétaCan
Menu
Back to cohort
Record W4386648721 · doi:10.1007/978-3-031-41456-5

Computational Collective Intelligence

2023· book· en· W4386648721 on OpenAlexfundno aff
Ngoc Thanh Nguyên, János Botzheim, László Gulyás, Manuel Núñez, Jan Treur, Gottfried Vossen, Adrianna Kozierkiewicz

Bibliographic record

VenueLecture notes in computer science · 2023
Typebook
Languageen
FieldComputer Science
TopicCognitive Computing and Networks
Canadian institutionsnot available
FundersNational University of Computer and Emerging SciencesUniversité de Technologie de TroyesUniversity of CarthageUniwersytet Śląski w KatowicachUniversité LavalZachodniopomorski Uniwersytet Technologiczny w SzczecinieUniwersytet Morski w GdyniEötvös Loránd TudományegyetemUniversidad Complutense de MadridSilesian University of TechnologyUniversidad de GranadaNational Taiwan University of Science and TechnologyUniversité de TunisUniverzita PardubiceUniversitatea Politehnica TimisoaraTrakya ÜniversitesiBirmingham City UniversityAristotle University of ThessalonikiYeungnam UniversityUniversiti Teknologi MalaysiaUniversité de Pau et des Pays de l'AdourWestfälische Wilhelms-Universität MünsterEuskal Herriko UnibertsitateaAcademia RomânaUniversità di BolognaUniversity of JordanUniversity of WollongongInha UniversityUniversity of UlsanCardiff UniversityAkademia Górniczo-Hutnicza im. Stanislawa StaszicaVrije Universiteit AmsterdamBournemouth UniversityUniversidad de AlmeríaUniversité Mohammed V de RabatBharathiar UniversityHøgskulen på VestlandetUniversity of CyprusInyuvesi Yakwazulu-NataliUniversidad Autónoma de MadridSlovenská technická univerzita v BratislaveNanyang Technological UniversitySouth Asian UniversityBudapesti Műszaki és Gazdaságtudományi EgyetemSlovenská Akadémia ViedPolitechnika KoszalińskaSwinburne University of TechnologyUniversity of Cape TownNational Taiwan UniversityOklahoma State UniversityUniversité de LorraineUniversity of OttawaVirginia Commonwealth University
KeywordsComputer scienceCollective intelligenceComputational intelligenceArtificial intelligence

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.007

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 head0.025
GPT teacher head0.275
Teacher spread0.250 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations8
Published2023
Admission routes1
Has abstractno

Explore more

Same venueLecture notes in computer scienceSame topicCognitive Computing and NetworksFrench-language works237,207