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Record W4232627304 · doi:10.1109/hri.2019.8673279

HRI'19 The 14th ACM/IEEE International Conference on Human-Robot Interaction

2019· article· en· W4232627304 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotics and Automated Systems
Canadian institutionsnot available
FundersU.S. Naval Research LaboratoryOffice of Naval ResearchUniversidade Federal do Espírito SantoNational Institute of InformaticsRyukoku UniversityIstituto Italiano di TecnologiaInternational Islamic University MalaysiaUniversity of TsukubaSyddansk UniversitetTechnion-Israel Institute of TechnologyUniversity of Colorado BoulderRitsumeikan UniversityDanmarks Tekniske UniversitetUniversity of WaterlooSapienza Università di RomaDongseo UniversityEscuela Colombiana de Ingeniería Julio GaravitoUniversity of TwenteMicrosoft ResearchTechnische Universiteit DelftTechnische Universiteit EindhovenUniversity of the West of EnglandOregon State UniversityUniversity of HertfordshireDe Montfort UniversitySamsungUniversity of Southern CaliforniaYonsei UniversityGeorge Mason UniversityYork UniversityUniversity of New South WalesHeriot-Watt UniversityHonda Research Institute, USAUniversity of WashingtonColorado School of MinesUniversity of Texas Rio Grande ValleyXiamen UniversityFuturewei TechnologiesMarquette UniversityVassar CollegeKent State UniversityLunds UniversitetWestern Michigan UniversityPennsylvania State UniversitySheffield Hallam UniversityKorea Institute of Science and TechnologyCarnegie Mellon UniversityNazarbayev UniversityUniversity of Central FloridaUniversitetet i OsloJohns Hopkins UniversityKeio UniversityWashington State UniversityUniversity of PennsylvaniaGeorgia Institute of TechnologyGeorge Washington UniversityÉcole Polytechnique Fédérale de LausanneVrije Universiteit BrusselTrinity College DublinMassachusetts Institute of TechnologyBrown UniversityOklahoma State UniversityUniversität HohenheimNew Mexico State UniversityYale UniversityAccenture
KeywordsComputer scienceHuman–robot interactionRobotHuman–computer interactionArtificial intelligence

Abstract

fetched live from OpenAlex

Conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. This may in some cases also include the cover art, table of contents, copyright statements, title-page or half title-pages, blank pages, venue maps or other general information relating to the conference that was part of the original conference proceedings.

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 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)0.004
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.160
Threshold uncertainty score0.534

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1600.084

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 head0.105
GPT teacher head0.336
Teacher spread0.231 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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