{"id":"W4230017155","doi":"10.5898/jhri.4.1.gleeson","title":"Tap and Push: Assessing the Value of Direct Physical Control in Human-Robot Collaborative Tasks","year":2015,"lang":"en","type":"article","venue":"Journal of Human-Robot Interaction","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Task (project management); Human–computer interaction; Computer science; Human–robot interaction; Robot control; Haptic technology; Simulation; Artificial intelligence; Engineering; Mobile robot","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005528131,0.0001380925,0.00038975,0.0001801353,0.0000724147,0.0001420774,0.0001045594,0.00005614183,0.00001489168],"category_scores_gemma":[0.00008868729,0.00009984858,0.00007022601,0.0001529485,0.00004850204,0.0006301993,0.0000119965,0.0003517755,0.000002969249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001566553,"about_ca_system_score_gemma":0.00004135392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004657919,"about_ca_topic_score_gemma":0.00005966557,"domain_scores_codex":[0.9987464,0.0001916324,0.0005863333,0.00008794838,0.0002640942,0.0001236042],"domain_scores_gemma":[0.9990118,0.0001766707,0.0003330225,0.0001073397,0.0003025733,0.00006859943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001144675,0.0003739836,0.003884312,0.00009741724,0.0003800974,0.00004814113,0.01452,0.2874586,0.6837384,0.001850194,0.003724129,0.003810292],"study_design_scores_gemma":[0.02114149,0.003978362,0.1139394,0.003210594,0.0008678432,0.001365424,0.05618495,0.6870155,0.0950981,0.001782791,0.01361456,0.001800932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907488,0.0005081316,0.002888656,0.000150309,0.001041067,0.000217151,0.000002733924,0.00002472724,0.004418445],"genre_scores_gemma":[0.9992822,0.00001463347,0.00009961955,0.00003185086,0.0004868682,0.000008639138,0.000001491587,0.00001866486,0.00005599982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5886403,"threshold_uncertainty_score":0.4071707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03525974082503899,"score_gpt":0.3464989844073001,"score_spread":0.3112392435822611,"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."}}