{"id":"W2126673703","doi":"10.1109/ccece.2007.222","title":"Mining Brain Tumors and Tracking their Growth Rates","year":2007,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Process (computing); Task (project management); Similarity (geometry); Brain tumor; Tracking (education); Artificial intelligence; Fractal; Magnetic resonance imaging; Data mining; Pattern recognition (psychology); Image (mathematics); Pathology; Radiology; Medicine; Mathematics","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":[0.0005696387,0.0000686842,0.0000690989,0.00006896712,0.00008054631,0.0001343992,0.0002412189,0.00002694629,0.000007468348],"category_scores_gemma":[0.00006625496,0.00005045101,0.00001915477,0.0002433642,0.00003757411,0.0003474017,0.00006943566,0.0000498902,0.000004022792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009487234,"about_ca_system_score_gemma":0.00001317879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007193897,"about_ca_topic_score_gemma":0.000002913448,"domain_scores_codex":[0.9994313,0.00001617713,0.0001308668,0.0001807747,0.00008584681,0.0001551092],"domain_scores_gemma":[0.9995281,0.0001894105,0.00003919741,0.0001359982,0.00005668655,0.00005057778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005308663,0.00003887302,0.005439056,0.00001963641,0.000007865062,0.00001796555,0.001992169,3.390925e-8,0.07987416,0.3121355,0.001393598,0.5990759],"study_design_scores_gemma":[0.00008314994,0.00003410503,0.02190569,0.00001587789,6.974556e-7,0.00002894824,0.0002704501,0.002739701,0.9664605,0.006735737,0.001588308,0.0001368335],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03116872,0.00007465846,0.9585229,0.002528458,0.00002754816,0.00005384785,1.331414e-7,0.0003305208,0.007293261],"genre_scores_gemma":[0.9479345,0.000007906353,0.05058876,0.0007591288,0.00002308338,0.000001439547,3.503988e-7,0.000003807105,0.0006810059],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9167658,"threshold_uncertainty_score":0.2057333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02431625573543874,"score_gpt":0.2734436103561474,"score_spread":0.2491273546207086,"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."}}