{"id":"W4413824988","doi":"10.1115/1.4069652","title":"Visual Telepresence for Underwater Manipulation","year":2025,"lang":"en","type":"article","venue":"Journal of Autonomous Vehicles and Systems","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute","funders":"Natural Science Foundation of Shandong Province; Natural Science Foundation of Jiangsu Province","keywords":"Underwater; Computer science; Human–computer interaction; Computer graphics (images); Geology; Oceanography","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":[0.0000694267,0.0003292296,0.0001820311,0.0002157926,0.0002342173,0.0002247699,0.0004187799,0.000270123,0.00312912],"category_scores_gemma":[0.0002520182,0.00009978881,0.0001453789,0.00009245216,0.0002643112,0.0003877348,0.0004364409,0.0002426334,0.0002613325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000154867,"about_ca_system_score_gemma":0.000235763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008855036,"about_ca_topic_score_gemma":0.001246773,"domain_scores_codex":[0.9999046,0.00001380974,0.00000389964,0.00002168248,0.00004424883,0.00001176809],"domain_scores_gemma":[0.999885,0.00002786623,0.00003192838,0.00001614242,0.00002698949,0.00001211068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000206522,0.00006928263,0.0007810986,0.0001972152,0.00001552972,0.0004724094,0.0001634638,0.007689118,0.7298657,0.002780225,0.00145612,0.2563033],"study_design_scores_gemma":[0.0001150918,0.002146895,0.01281441,0.000120233,0.0001049633,0.003595216,0.0002771474,0.4085805,0.5207328,0.003771277,0.04762824,0.0001132751],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2281024,0.001232855,0.7521039,0.0002508454,0.0002215194,0.0001147475,0.0000713188,0.001899668,0.01600278],"genre_scores_gemma":[0.9188243,0.0003495933,0.07467549,0.00008994178,0.00006580991,0.00005342012,0.00004301783,0.00003866695,0.005859619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00312912,"threshold_uncertainty_score":0.01046795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04698535341013525,"score_gpt":0.3233040970836571,"score_spread":0.2763187436735219,"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."}}