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Record W2006591816 · doi:10.1504/ijart.2012.046278

Let robots do the talking

2012· article· en· W2006591816 on OpenAlexfundno aff
Sjef Fransen, Panos Markopoulos

Bibliographic record

VenueInternational Journal of Arts and Technology · 2012
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
FundersCanadian Institute for Theoretical Astrophysics
KeywordsFacilitatorRobotProtocol (science)Computer scienceAsk priceHuman–computer interactionArtificial intelligenceTest (biology)Intervention (counseling)PsychologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

This paper describes an investigation of different variations of the robotic intervention protocol, a method for obtaining verbalisation data from children during evaluation that involves using a social robot as a proxy for a test facilitator to prompt, ask and help children, and thus encouraging them to verbalise their thoughts and experiences. A number of variations of this verbalisation protocol were implemented and tried out, leading to guidelines for the application of the method and for the implementation of social robots aimed to support it.

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)0.003
metaresearch head score (Gemma)0.014
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: Other
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.005
Scholarly communication0.0030.005
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0320.017

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 head0.021
GPT teacher head0.391
Teacher spread0.369 · 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
Published2012
Admission routes1
Has abstractyes

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