{"id":"W4362487604","doi":"10.1117/12.2654217","title":"Tracked tissue sensing for tumor bed inspection","year":2023,"lang":"en","type":"article","venue":"","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Testbed; Computer science; Breast-conserving surgery; Breast tissue; Pipeline (software); Biomedical engineering; Computer vision; Artificial intelligence; Medicine; Breast cancer; Cancer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005050823,0.0003078977,0.0002189653,0.0003826038,0.0002348206,0.0004447798,0.0006311364,0.0004651284,0.001744812],"category_scores_gemma":[0.002439017,0.0001872987,0.0001898245,0.000233415,0.000423813,0.0006198493,0.0006595398,0.0002457666,0.0002907119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005532161,"about_ca_system_score_gemma":0.0007095727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002175276,"about_ca_topic_score_gemma":0.002195489,"domain_scores_codex":[0.9995517,0.00007051367,0.00001941011,0.0001033785,0.0002029112,0.00005203111],"domain_scores_gemma":[0.999156,0.0003154614,0.0001560218,0.0001329684,0.0001697132,0.0000698647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007482106,0.0003250962,0.007878758,0.0002705067,0.00004096913,0.0004253458,0.0002312791,0.1006262,0.7608158,0.002494837,0.001987212,0.1241557],"study_design_scores_gemma":[0.00005397473,0.001660289,0.008851187,0.00002997741,0.00002908465,0.0007319043,0.0001091846,0.7231647,0.2592274,0.001346729,0.004744357,0.0000511875],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5614592,0.0006563452,0.4302006,0.0003356132,0.0001830525,0.0002445201,0.0003272659,0.003357931,0.003235456],"genre_scores_gemma":[0.9343339,0.0001794875,0.06422127,0.00008746928,0.0000113822,0.0000571918,0.0001578098,0.00004716081,0.0009043962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002175276,"threshold_uncertainty_score":0.005836964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06394092974565083,"score_gpt":0.3596855586840828,"score_spread":0.2957446289384319,"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."}}