MétaCan
Menu
Back to cohort
Record W4392964111 · doi:10.1007/978-3-031-56027-9

Advances in Information Retrieval

2024· book· en· W4392964111 on OpenAlexfundno aff

Bibliographic record

VenueLecture notes in computer science · 2024
Typebook
Languageen
FieldComputer Science
TopicInformation Retrieval and Search Behavior
Canadian institutionsnot available
FundersUniversitat Politècnica de ValènciaNational Institute of Standards and TechnologyHaute école Spécialisée de Suisse OccidentaleInstitut National des Sciences Appliquées de LyonUniversity of North Carolina at Chapel HillUniversität Duisburg-EssenUniversidade Federal de Minas GeraisUniversity of Cape TownInstituto Superior TécnicoTsinghua UniversityChinese Academy of SciencesUniversité de Bretagne OccidentaleUniversity of Massachusetts AmherstUniversità degli Studi di TorinoUniversità di BolognaRenmin University of ChinaUniversidade de LisboaAix-Marseille UniversitéUniversidade Nova de LisboaUniversität RegensburgUniversity of WaterlooRadboud UniversiteitUniversität InnsbruckTechnische Universiteit DelftUniversiteit van AmsterdamTechnische Universität WienUniversity of QueenslandYork UniversityUniversity of GlasgowUniversiteit LeidenEberhard Karls Universität TübingenUniversità degli Studi di PadovaUniversity of MelbourneUniversitetet i StavangerUniversité Grenoble AlpesDublin City UniversityQatar UniversityUniversità Ca' Foscari VeneziaPhilipps-Universität MarburgUniversity of Chinese Academy of SciencesCentre National de la Recherche ScientifiqueUniverzita Karlova v PrazeUniversità degli Studi di CagliariSorbonne UniversitéIndian National Science AcademyUniversidad Nacional de Educación a DistanciaUniversidade da CoruñaRMIT UniversityCarnegie 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".

Quick stats

Citations17
Published2024
Admission routes1
Has abstractno

Explore more

Same venueLecture notes in computer scienceSame topicInformation Retrieval and Search BehaviorFrench-language works237,207