{"id":"W2069509221","doi":"10.1016/j.ejmp.2008.01.006","title":"Identification of intratumour low frequency microvascular components via BOLD signal fractal dimension mapping","year":2008,"lang":"en","type":"article","venue":"Physica Medica","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Juravinski Cancer Centre; St. Joseph’s Healthcare Hamilton; McMaster University","funders":"","keywords":"Fractal dimension; Fractal; Dynamic contrast; A priori and a posteriori; SIGNAL (programming language); Dimension (graph theory); Parametric statistics; Contrast (vision); Magnetic resonance imaging; Blood-oxygen-level dependent; Pattern recognition (psychology); Fractal analysis; Computer science; Artificial intelligence; Mathematics; Medicine; Radiology; Mathematical analysis; Statistics","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":[0.0001239479,0.0001245479,0.0001114797,0.0007182529,0.0001018283,0.0002534025,0.00009586298,0.0002168686,0.0007189651],"category_scores_gemma":[0.0004842798,0.00008917136,0.00008867496,0.0002216356,0.0001558264,0.0003364508,0.0001333845,0.0001643954,0.0001232892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007381308,"about_ca_system_score_gemma":0.00007002185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002045174,"about_ca_topic_score_gemma":0.0002514238,"domain_scores_codex":[0.9999751,0.000007000974,0.000001250543,0.000005082618,0.000006352806,0.000005292157],"domain_scores_gemma":[0.9998624,0.00007795093,0.00001972913,0.00001080772,0.00001879997,0.00001021745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003813267,0.00004370887,0.01085835,0.0001599213,0.00002524046,0.0002971787,0.0001200626,0.001909227,0.8815941,0.001686782,0.000355363,0.1025688],"study_design_scores_gemma":[0.00004961455,0.0006330158,0.1731607,0.00004554789,0.0001772944,0.005223203,0.0004400131,0.2362928,0.5699263,0.007751018,0.006223825,0.00007679851],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8772106,0.001078523,0.11884,0.0001980443,0.00002113767,0.00003582973,0.0001601626,0.0001191469,0.002336581],"genre_scores_gemma":[0.9725127,0.0004142924,0.02623435,0.00002546729,0.00002082711,0.00002576744,0.00006123612,0.00001491078,0.0006903474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007189651,"threshold_uncertainty_score":0.002405107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744392124994728,"score_gpt":0.2476607554580292,"score_spread":0.2302168342080819,"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."}}