Personal Care Robots for Children: State of the Art
Bibliographic record
Abstract
In the last decades, the application of robots in variety of industries has remarkably been increased. Self-governing robots have been employed in various fields of human life, particularly in that of old and very young people. It is assumed that in the succeeding years, personal care robots will be in an intimate relation with human beings. But, what caring responsibilities will the future robots have before children at home? This is directly related to the kinds of robots as well as those aspects of getting old that are the matter of question. Among the topics that are germane to robot carers, Child-care is the least discussed one. In this article the duties of care robots in the life of youth is investigated. It studies the benefits of the application of robots in daily life along with the negative points, perils, and anxieties that rise from the application. In this article, we examine the benefits of the usage of robots in the child life. Besides, we will discuss the disadvantages, dangers and fears that are related to child-robot connections. In the end, we will recommend some useful points.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".