{"id":"W2965099042","doi":"10.1007/s40846-019-00482-x","title":"Mechanical Characterization of Soft Tissue Constituents for Cancer Detection","year":2019,"lang":"en","type":"article","venue":"Journal of Medical and Biological Engineering","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Elastography; Soft tissue; Biomedical engineering; Materials science; Stiffness; Biological tissue; Breast cancer; Human breast; Cancer; Pathology; Acoustics; Ultrasound; Medicine; Physics; Composite material","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":[0.0002158279,0.00006361992,0.0002005116,0.00003637428,0.000008548006,0.000006216585,0.00006215996,0.0001488142,0.00005604347],"category_scores_gemma":[0.0001014525,0.00004356608,0.00003174746,0.00003413275,0.00001293589,0.00005042705,0.0000153317,0.0001200785,5.675258e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001130374,"about_ca_system_score_gemma":0.000008762571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001327862,"about_ca_topic_score_gemma":4.141044e-7,"domain_scores_codex":[0.999456,0.000005476189,0.0002648866,0.00004830148,0.000132923,0.00009235842],"domain_scores_gemma":[0.9997441,0.00006662008,0.000046848,0.00002108704,0.00004014164,0.00008120671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002786923,0.000009757291,0.00004107463,0.0001614255,0.00002306289,0.000001686309,0.000009371644,0.005931882,0.9774967,0.0002974325,8.289669e-7,0.01599892],"study_design_scores_gemma":[0.001262415,0.0006090094,0.001519628,0.0006926859,0.00003928071,0.0001019543,0.00001385599,0.5793173,0.4101802,0.000127631,0.005922949,0.0002131594],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6958694,0.00009856127,0.3032376,0.00004524307,0.0006805843,0.00004781859,0.00000425874,0.00001416922,0.000002351372],"genre_scores_gemma":[0.9988961,0.0004339264,0.0004285923,0.00001734564,0.0002130509,0.000002685421,0.000001517712,0.000004983405,0.000001825649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5733854,"threshold_uncertainty_score":0.1776573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01275618929118868,"score_gpt":0.2247476797634694,"score_spread":0.2119914904722807,"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."}}