{"id":"W2921503204","doi":"10.1117/1.jbo.24.3.036006","title":"Slope-based segmentation of articular cartilage using polarization-sensitive optical coherence tomography phase retardation image","year":2019,"lang":"en","type":"article","venue":"Journal of Biomedical Optics","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Foundation of Korea; Canadian Institutes of Health Research; National Research Foundation; California HIV/AIDS Research Program","keywords":"Optical coherence tomography; Birefringence; Materials science; Cartilage; Articular cartilage; Biomedical engineering; Optics; Anatomy; Osteoarthritis; Medicine; Pathology; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003993573,0.0001676297,0.0003519462,0.0003945431,0.00003660782,0.00004202254,0.0001736833,0.0001494698,0.00009639702],"category_scores_gemma":[0.0001124962,0.0001552796,0.0001922712,0.001015414,0.0002599135,0.0003165917,0.00001863791,0.0002977658,0.00001243252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007177748,"about_ca_system_score_gemma":0.0001056437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001642886,"about_ca_topic_score_gemma":4.245312e-7,"domain_scores_codex":[0.9980463,0.00005156341,0.0008535009,0.0001371986,0.0006748384,0.0002366094],"domain_scores_gemma":[0.9985454,0.0001822147,0.000290102,0.0002139236,0.000519825,0.0002485435],"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":[0.00004845803,0.0002774609,0.0003878786,0.00009466452,0.00007679766,0.00001509287,0.0001025819,0.003772755,0.9933143,0.0003783882,0.00002793662,0.001503705],"study_design_scores_gemma":[0.002472677,0.000765387,0.001064082,0.0002288599,0.0003061903,0.00003775486,0.0003218883,0.3045544,0.6896327,0.0002507478,0.00007790137,0.0002874459],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6346941,0.00003983729,0.364581,0.00008038379,0.0001619003,0.0002131735,0.00002560261,0.00002567326,0.0001783451],"genre_scores_gemma":[0.8666638,0.00001023253,0.1331753,0.00003046654,0.00006328953,0.000002673023,0.00003114541,0.00002108681,0.000002030237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3036816,"threshold_uncertainty_score":0.6332119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01038585552040916,"score_gpt":0.2619831820775153,"score_spread":0.2515973265571061,"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."}}