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Record W4392887246 · doi:10.1007/978-3-031-56060-6

Advances in Information Retrieval

2024· book· en· W4392887246 on OpenAlexfundno aff

Bibliographic record

VenueLecture notes in computer science · 2024
Typebook
Languageen
FieldComputer Science
TopicInformation Retrieval and Search Behavior
Canadian institutionsnot available
FundersUniversity of North Carolina at Chapel HillNational Institute of Standards and TechnologyUniversity of Chinese Academy of SciencesInstitut National des Sciences Appliquées de LyonUniversität Duisburg-EssenUniversity of Massachusetts AmherstUniversità degli Studi di TorinoUniversità di BolognaAix-Marseille UniversitéUniversidade Nova de LisboaUniversität RegensburgUniversitetet i BergenUniversidade de Santiago de CompostelaUniversità degli Studi di CagliariTechnische Universität BraunschweigUniversidade Federal de Minas GeraisRadboud UniversiteitUniversity of WaterlooInstituto Superior TécnicoUniversité de Bretagne OccidentaleTsinghua UniversityChinese Academy of SciencesUniversidade de LisboaRenmin University of ChinaUniversität InnsbruckTechnische Universiteit DelftTechnische Universität WienUniversity of QueenslandUniversity of MelbourneUniversiteit van AmsterdamUniverzita Karlova v PrazeUniversity College DublinHaute école Spécialisée de Suisse OccidentaleUniversity of SouthamptonUniversidade da CoruñaUniversidad Nacional de Educación a DistanciaTU Graz, Internationale Beziehungen und MobilitätsprogrammeUniversity of GlasgowEberhard Karls Universität TübingenYork UniversityUniversity of CyprusUniversitetet i StavangerUniversité Grenoble AlpesSeoul National UniversityUniversidade do PortoDublin City UniversityCentre National de la Recherche ScientifiqueUniversity of RoehamptonUniversità degli Studi di PadovaJohns Hopkins UniversityUniversità Ca' Foscari VeneziaQatar UniversityTechnische Universität BerlinGeorgetown UniversityIndian National Science AcademyCarnegie Mellon UniversityUniversity of Southern Maine
KeywordsComputer scienceInformation retrieval

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.010
Science and technology studies0.0010.001
Scholarly communication0.0050.008
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0610.067

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 head0.010
GPT teacher head0.266
Teacher spread0.255 · 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 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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Citations4
Published2024
Admission routes1
Has abstractno

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