{"id":"W2124171640","doi":"10.1111/j.1365-2818.2011.03535.x","title":"Segmentation of epithelium in H&E stained odontogenic cysts","year":2011,"lang":"en","type":"article","venue":"Journal of Microscopy","topic":"Oral and Maxillofacial Pathology","field":"Dentistry","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Saskatchewan","funders":"","keywords":"Segmentation; Artificial intelligence; Epithelium; Pathology; Epithelial tissue; Image segmentation; Anatomy; Pattern recognition (psychology); Computer science; Mathematics; Biology; Computer vision; Medicine","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":[0.00100173,0.0005479988,0.0007510196,0.001595802,0.0004850902,0.0009699382,0.0007076123,0.0007855521,0.0008978804],"category_scores_gemma":[0.001506179,0.0006933282,0.0003931318,0.0008091276,0.0005248887,0.0004410918,0.0004954091,0.0005518979,0.0005771803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005483112,"about_ca_system_score_gemma":0.0009008865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002384924,"about_ca_topic_score_gemma":0.004969851,"domain_scores_codex":[0.9995713,0.00007426034,0.00004387377,0.0001059295,0.0001564882,0.00004824611],"domain_scores_gemma":[0.9994528,0.0002332981,0.00008378027,0.00006647074,0.0001348856,0.00002879703],"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":[0.0002140874,0.00007219806,0.002344115,0.0002406965,0.00003981752,0.0004821476,0.0002388323,0.01740633,0.8338861,0.000659675,0.0004871202,0.1439288],"study_design_scores_gemma":[0.00004806694,0.000221708,0.03085099,0.00007171933,0.00007697546,0.001964057,0.0003166905,0.2264197,0.7271715,0.002948567,0.009801281,0.0001088538],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.281015,0.0008845203,0.7143605,0.0001119484,0.00003490038,0.000289252,0.0002791849,0.001859938,0.001164677],"genre_scores_gemma":[0.174858,0.0004514587,0.8226939,0.00005032884,0.000007666663,0.0001540446,0.0003924732,0.0002617719,0.001130405],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002384924,"threshold_uncertainty_score":0.00529772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04267271578482782,"score_gpt":0.3147650665213734,"score_spread":0.2720923507365455,"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."}}