{"id":"W2405420781","doi":"10.1158/1538-7445.sabcs15-p4-03-05","title":"Abstract P4-03-05: Wide-field optical coherence tomography (WF-OCT) for near real-time, point-of-care assessment of margin status in breast-conserving surgery specimens: Results of a feasibility study at a high-volume single-centre","year":2016,"lang":"en","type":"article","venue":"Cancer Research","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Lumpectomy; Optical coherence tomography; Breast-conserving surgery; Medicine; Breast cancer; Margin (machine learning); Surgical margin; Nuclear medicine; Radiology; Mastectomy; Cancer; Surgery; Computer science; Resection","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001672565,0.0002561431,0.0006972628,0.0004769124,0.00007725135,0.0000350455,0.0004444475,0.0001644621,0.0004314972],"category_scores_gemma":[0.0005441598,0.0002261299,0.0002170647,0.001430974,0.0004753767,0.0001908136,0.0002022956,0.0003401958,0.000006966842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006654802,"about_ca_system_score_gemma":0.000461088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002016602,"about_ca_topic_score_gemma":0.001909254,"domain_scores_codex":[0.9963322,0.0002036403,0.001098062,0.0006305889,0.0008554922,0.0008799946],"domain_scores_gemma":[0.9928375,0.004821595,0.0001735948,0.0009842211,0.0009217559,0.0002612642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00226576,0.001639776,0.6967229,0.001594695,0.0002302898,0.00001598763,0.0008212801,0.0004295192,0.2851222,0.0002210438,0.002844275,0.008092344],"study_design_scores_gemma":[0.002604722,0.0007002923,0.9583126,0.00119308,0.00004019051,9.493399e-7,0.0009390853,0.0004168526,0.03507076,0.0002853248,0.00009053528,0.0003455642],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942089,0.0001728935,0.00008413693,0.0004488178,0.00006545633,0.002615907,0.001059875,0.00006389545,0.001280172],"genre_scores_gemma":[0.9970322,0.00008781348,0.002243514,0.00000358218,0.00002688777,0.0005007744,0.00002191605,0.00004558073,0.0000377321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2615898,"threshold_uncertainty_score":0.9221308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05090446393164681,"score_gpt":0.3468311960753269,"score_spread":0.2959267321436801,"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."}}