{"id":"W1582311982","doi":"10.1007/978-3-540-70521-5_18","title":"Estimation of the Fracture Toughness of Soft Tissue from Needle Insertion","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":102,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Fracture toughness; Fracture mechanics; Materials science; Penetration (warfare); Soft tissue; Work (physics); Fracture (geology); Toughness; Computer science; Biomedical engineering; Mechanics; Composite material; Mechanical engineering; Surgery; Engineering; Physics","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":[0.00005248222,0.0001473167,0.0001958407,0.0001023706,0.00005278085,0.00001617469,0.0004762661,0.0001591573,0.00001274293],"category_scores_gemma":[0.00002323374,0.0001156683,0.00004248718,0.0002014047,0.0002135947,0.00006642571,0.00008183983,0.000238087,0.000003116305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005010183,"about_ca_system_score_gemma":0.00005718441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004939047,"about_ca_topic_score_gemma":0.0000212563,"domain_scores_codex":[0.9991784,0.000003664521,0.0002411124,0.0002011043,0.0002698083,0.0001059073],"domain_scores_gemma":[0.9992291,0.0001497449,0.0001078406,0.0004282125,0.00006233233,0.00002276125],"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":[5.068263e-7,0.000004770209,0.00002596315,0.00001815835,0.000003546067,2.865193e-7,0.000334069,0.8894486,0.0008103951,0.0001120088,0.00002301391,0.1092187],"study_design_scores_gemma":[0.00007031267,0.00001432267,0.002362446,0.0002234852,0.0000103488,0.000003248703,1.404366e-7,0.9408407,0.03838967,0.01724918,0.000674293,0.0001618938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004720908,0.0002966011,0.9939905,0.0001026896,0.0003721385,0.0001710065,0.00001238033,0.0000341753,0.0002995335],"genre_scores_gemma":[0.958617,0.00002339918,0.04112841,0.00007990387,0.000102485,0.000003156337,0.00001025251,0.00001656506,0.00001881077],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9538961,"threshold_uncertainty_score":0.4716817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01064350768650493,"score_gpt":0.2201224056082491,"score_spread":0.2094788979217442,"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."}}