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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.564
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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