{"id":"W3169700178","doi":"10.32920/ryerson.14650065.v1","title":"Development Of A Graphical User Interface For Control Of A Robotic Manipulatior With Sample Acquisition Capability","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Joystick; Graphical user interface; Computer science; Human–computer interaction; Robotic arm; User interface; Graphical user interface testing; Task (project management); Interface (matter); User interface design; Simulation; Artificial intelligence; User experience design; Engineering; Operating system; Systems engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006940485,0.0006676475,0.0004307527,0.0005612636,0.0001766632,0.0007418137,0.001480297,0.0006938176,0.009468131],"category_scores_gemma":[0.001661974,0.0003000082,0.0004565765,0.0001880443,0.0002106413,0.0005331938,0.0005073294,0.0007335334,0.002931093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001379384,"about_ca_system_score_gemma":0.0003781936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003409035,"about_ca_topic_score_gemma":0.0003207572,"domain_scores_codex":[0.9994701,0.00008694432,0.00003815031,0.00009979821,0.0002722807,0.00003285554],"domain_scores_gemma":[0.999157,0.0002933444,0.0000500911,0.0001053338,0.0003396153,0.00005462681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005178374,0.0003103328,0.001192302,0.001054873,0.00007998754,0.001040775,0.0008571212,0.008237,0.468115,0.006970573,0.01686493,0.4947593],"study_design_scores_gemma":[0.0003968302,0.002249898,0.0100024,0.0003425205,0.0001926518,0.005001192,0.0002338616,0.2792988,0.4601825,0.003295118,0.2385778,0.0002264065],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01094954,0.0001327466,0.9689577,0.00008651784,0.00006453646,0.0004132524,0.0001798834,0.01431514,0.00490076],"genre_scores_gemma":[0.1164751,0.0002435734,0.8653717,0.0001819653,0.00004573153,0.0008473515,0.0008010606,0.001237771,0.01479577],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009468131,"threshold_uncertainty_score":0.03167409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0451806606015378,"score_gpt":0.3619071995213973,"score_spread":0.3167265389198595,"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."}}