{"id":"W1593374505","doi":"10.1007/978-3-642-04268-3_7","title":"A Computer Model of Soft Tissue Interaction with a Surgical Aspirator","year":2009,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Aspirator; Computer science; Surgical simulation; Haptic technology; Imaging phantom; Soft tissue; Rendering (computer graphics); Surgical procedures; Simulation; Virtual reality; Biomedical engineering; Computer graphics (images); Surgery; Human–computer interaction; Medicine; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007802713,0.00009145157,0.0001155019,0.0001050904,0.00003550055,0.00004405571,0.0002177339,0.00003458991,0.000002213981],"category_scores_gemma":[0.00000374925,0.00007453963,0.00001506535,0.0005273543,0.00007455399,0.0001208882,0.00002657108,0.0001242416,0.000002554128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003570054,"about_ca_system_score_gemma":0.00002895761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003643055,"about_ca_topic_score_gemma":0.00000684261,"domain_scores_codex":[0.9993527,0.00000430209,0.0001325944,0.000191007,0.0001550742,0.0001643476],"domain_scores_gemma":[0.9996295,0.00006283097,0.00002250487,0.0001923395,0.0000471411,0.00004568389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001915143,0.00001957836,0.00007140204,0.000004074154,0.000001065203,0.000001862026,0.0001432899,0.839727,0.002132543,0.0001177976,0.000003445022,0.157776],"study_design_scores_gemma":[0.0001328476,0.00008675663,0.0003756701,0.00002945456,0.000001723476,0.00001551107,1.234374e-7,0.9865789,0.01150034,0.001155484,0.0000310443,0.00009214613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1240237,0.00002000806,0.8755615,0.0001410903,0.00008343207,0.00008264419,7.080987e-7,0.00006588698,0.00002105946],"genre_scores_gemma":[0.7579788,9.870588e-7,0.2418475,0.00009980168,0.00006574052,0.000002370371,5.657924e-7,0.000004085066,1.532198e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6339551,"threshold_uncertainty_score":0.3039638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01300965996966414,"score_gpt":0.2501073879345396,"score_spread":0.2370977279648754,"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."}}