{"id":"W4386989897","doi":"10.3850/978-981-18-8071-1_p241-cd","title":"Understanding and Quantifying Human Factors in Programming from Demonstration: A User Study Proposal","year":2023,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Canadian Institute of Steel Construction","keywords":"Computer science; Human–computer interaction; Field (mathematics); Robot; Human–robot interaction; Perspective (graphical); Process (computing); Artificial intelligence; Robotics; Transfer of learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01892041,0.001009725,0.0007257322,0.0009553623,0.0007909781,0.001715552,0.001188571,0.001622815,0.003800625],"category_scores_gemma":[0.06594577,0.0006257283,0.0007613809,0.0005354061,0.001627079,0.001975412,0.001827895,0.0008187282,0.0006310284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005247869,"about_ca_system_score_gemma":0.0006288413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008152332,"about_ca_topic_score_gemma":0.0008306345,"domain_scores_codex":[0.9887487,0.007988375,0.0008013669,0.001025159,0.001079647,0.0003567589],"domain_scores_gemma":[0.8711824,0.1103408,0.002154934,0.007121204,0.008038182,0.001162429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0126845,0.02729538,0.2853175,0.005438927,0.0006917834,0.001584584,0.1013475,0.009686623,0.1577765,0.008002196,0.003143168,0.3870315],"study_design_scores_gemma":[0.002766758,0.1182766,0.5468638,0.0009118951,0.001854353,0.005900562,0.04518275,0.09454487,0.1454907,0.01073498,0.0264525,0.001020238],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"protocol","genre_scores_codex":[0.9430469,0.0001758691,0.05178583,0.0001931881,0.00002367212,0.002058149,0.0002385634,0.0002621014,0.002215659],"genre_scores_gemma":[0.9505129,0.0001265055,0.04486191,0.0001535852,0.00001631339,0.002673061,0.0001594091,0.00005800501,0.001438203],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.01892041,"threshold_uncertainty_score":0.1000619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2457366780117788,"score_gpt":0.328437842270853,"score_spread":0.08270116425907428,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}