{"id":"W3152390953","doi":"","title":"Computerized cancer malignancy grading of fine needle aspirates","year":2009,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Malignancy; Grading (engineering); Breast cancer; Medicine; Radiology; Cancer; Stage (stratigraphy); Biopsy; Oncology; Internal 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":[0.00110406,0.0004693992,0.0004300305,0.006471257,0.0003475421,0.001282269,0.0006730193,0.0005084875,0.003495542],"category_scores_gemma":[0.006021909,0.000231976,0.0005227452,0.002611188,0.0003444768,0.0004805205,0.0006701004,0.0003573837,0.00170407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009215904,"about_ca_system_score_gemma":0.0005594299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005497241,"about_ca_topic_score_gemma":0.00503597,"domain_scores_codex":[0.9980013,0.0002269462,0.0002242295,0.0002350335,0.001200255,0.0001121887],"domain_scores_gemma":[0.9975603,0.0005342055,0.0003831937,0.0001991773,0.001221392,0.0001017319],"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":[0.001458385,0.0001687895,0.2820979,0.001262357,0.0002536831,0.002654814,0.0006353938,0.005332057,0.1074753,0.003243471,0.01556318,0.5798546],"study_design_scores_gemma":[0.000115499,0.001111993,0.7212214,0.0004185842,0.0004617102,0.01558547,0.0006306504,0.05313357,0.108218,0.003277167,0.09557082,0.0002551333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7264017,0.02283071,0.1746818,0.0008525096,0.0007660741,0.002902077,0.01279074,0.005789871,0.05298442],"genre_scores_gemma":[0.8970831,0.004665488,0.07829528,0.0002773739,0.0001334383,0.0005595284,0.007767327,0.0001931065,0.01102535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006471257,"threshold_uncertainty_score":0.01169378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03115059223263779,"score_gpt":0.2919112792150696,"score_spread":0.2607606869824318,"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."}}