{"id":"W2139590107","doi":"10.1002/rcs.169","title":"Feasibility of locating tumours in lung via kinaesthetic feedback","year":2008,"lang":"en","type":"article","venue":"International Journal of Medical Robotics and Computer Assisted Surgery","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; London Health Sciences Centre","funders":"","keywords":"Palpation; Parenchyma; Lung; Stiffness; Medicine; Nuclear medicine; In vivo; Biomedical engineering; Radiology; Pathology; Materials science; Biology; Internal medicine","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":[0.0004332839,0.00009759759,0.0002930753,0.0002015152,0.00002110905,0.00001789322,0.0002643573,0.00008149897,0.00001560757],"category_scores_gemma":[0.00009282412,0.00008965766,0.000108763,0.0001457634,0.00009198466,0.00006366122,0.00005425228,0.0002772737,8.004903e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006408431,"about_ca_system_score_gemma":0.00009684179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001209657,"about_ca_topic_score_gemma":0.00000427326,"domain_scores_codex":[0.9983242,0.00003258445,0.000718743,0.00009001885,0.0007102024,0.0001243047],"domain_scores_gemma":[0.998965,0.000417834,0.0001653919,0.00008619446,0.0002200454,0.0001454905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004299539,0.0007009734,0.582825,0.0001492432,0.0002617893,0.0008155622,0.0005363054,0.3170149,0.0001437041,0.001289873,0.002589982,0.09362967],"study_design_scores_gemma":[0.0004736328,0.00001916396,0.3930984,0.0003959616,0.00001338398,0.001065517,0.00002236759,0.6043929,0.00004894615,0.0002942986,0.0000523854,0.0001230335],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.676456,0.0005920457,0.320614,0.001270798,0.0009618564,0.000044039,0.000001619682,0.00001537426,0.00004429309],"genre_scores_gemma":[0.9936724,0.0004453507,0.005592416,0.00007391132,0.0001991639,9.292456e-7,0.000002963663,0.00001112801,0.000001706167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3172165,"threshold_uncertainty_score":0.3656133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02822768537266263,"score_gpt":0.2705641831358307,"score_spread":0.2423364977631681,"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."}}