{"id":"W4301387036","doi":"10.48550/arxiv.1701.03779","title":"Tumour Ellipsification in Ultrasound Images for Treatment Prediction in\\n Breast Cancer","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Terry Fox Foundation","keywords":"Contouring; Computer science; Artificial intelligence; Region of interest; Segmentation; Pattern recognition (psychology); Support vector machine; Ultrasound; Computer vision; Feature (linguistics); Feature extraction; Breast cancer; Cancer; Radiology; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004936998,0.0003859815,0.0003932281,0.00121506,0.0001707016,0.0004812271,0.0003372819,0.0005704407,0.001034484],"category_scores_gemma":[0.001956963,0.000185628,0.0003328707,0.0005914372,0.0002004186,0.0003495767,0.0002812856,0.0002758679,0.0006455641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002013802,"about_ca_system_score_gemma":0.0002411976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00229338,"about_ca_topic_score_gemma":0.003576927,"domain_scores_codex":[0.9996794,0.00009271233,0.00002005209,0.00006630124,0.0001107674,0.00003083894],"domain_scores_gemma":[0.9993882,0.0003278737,0.00008129571,0.0000573978,0.0001180482,0.00002723242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007308513,0.0002372665,0.01095149,0.0003263053,0.00007471066,0.0004164463,0.0002649511,0.04277853,0.2770642,0.0005532113,0.002719555,0.6638824],"study_design_scores_gemma":[0.00003474962,0.0003653703,0.03830086,0.00004394159,0.0000824029,0.0008318216,0.0001964505,0.8347387,0.1204437,0.0005592635,0.004351828,0.00005090105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.544811,0.003307992,0.4430169,0.0004110642,0.0001185586,0.0002289246,0.0004895205,0.004833524,0.002782721],"genre_scores_gemma":[0.8394313,0.001241001,0.1565496,0.0001206458,0.000057984,0.0000725145,0.000678303,0.0001353263,0.001713412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00229338,"threshold_uncertainty_score":0.004560113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07290549991499964,"score_gpt":0.2232271426290522,"score_spread":0.1503216427140525,"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."}}