{"id":"W2020932463","doi":"10.1007/s00330-007-0843-3","title":"Diffusion-weighted MRI in cervical cancer","year":2008,"lang":"en","type":"article","venue":"European Radiology","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":235,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Medicine; Cervix; Effective diffusion coefficient; Cervical cancer; Stage (stratigraphy); Diffusion MRI; Radiology; Nuclear medicine; Neuroradiology; Percentile; Cancer; Magnetic resonance imaging; Internal medicine; Neurology","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":[0.001063725,0.0002804307,0.0002849355,0.002242365,0.000568825,0.0007455429,0.0006169448,0.00165697,0.002791821],"category_scores_gemma":[0.004996037,0.0002431125,0.0002282145,0.001133925,0.00103943,0.001343744,0.0004457112,0.0006260689,0.0007147752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001099844,"about_ca_system_score_gemma":0.001142811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004939637,"about_ca_topic_score_gemma":0.003990634,"domain_scores_codex":[0.9997676,0.00008468481,0.00004086714,0.00002961723,0.00003226782,0.00004495372],"domain_scores_gemma":[0.9993988,0.000259633,0.0000752343,0.00005420904,0.0001439041,0.00006828005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001754319,0.0004228788,0.2092158,0.004469322,0.0003925063,0.2088125,0.002181832,0.001876949,0.07399843,0.01519249,0.0442079,0.4374751],"study_design_scores_gemma":[0.0001629552,0.0008346883,0.2753105,0.001800296,0.0005630815,0.4558728,0.00284841,0.002394614,0.02271687,0.01333382,0.2240292,0.0001327311],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5497307,0.2707784,0.003226926,0.02909924,0.001274922,0.0001488471,0.0003636338,0.0001287921,0.1452486],"genre_scores_gemma":[0.9140757,0.07255067,0.003000155,0.002196136,0.001741113,0.00004503017,0.0001999384,0.00004940317,0.006141927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004939637,"threshold_uncertainty_score":0.009821773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02632931243552148,"score_gpt":0.2805114113895725,"score_spread":0.254182098954051,"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."}}