{"id":"W2103808961","doi":"10.1158/1078-0432.ccr-06-2379","title":"Characterization and Magnetic Resonance Imaging of a Rat Model of Human B-Cell Central Nervous System Lymphoma","year":2007,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"CNS Lymphoma Diagnosis and Treatment","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Immunovaccine (Canada)","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Magnetic resonance imaging; Central nervous system; Lymphoma; Pathology; Characterization (materials science); Primary central nervous system lymphoma; Nuclear magnetic resonance; Medicine; Neuroscience; Biology; Radiology; Materials science; Nanotechnology; Physics","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":[0.0002558207,0.0005837317,0.0003708857,0.0006581694,0.0001601217,0.0002283144,0.0003104051,0.0003433326,0.001577099],"category_scores_gemma":[0.0001433572,0.0001639843,0.0002175913,0.0002412611,0.0002939983,0.0002930271,0.0001602108,0.0005567075,0.0006574556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003729988,"about_ca_system_score_gemma":0.0002758143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001768407,"about_ca_topic_score_gemma":0.00219169,"domain_scores_codex":[0.9998267,0.00003004716,0.000009913057,0.00003758328,0.0000569941,0.00003886289],"domain_scores_gemma":[0.9998318,0.00002139625,0.00004712266,0.00002949161,0.00002915779,0.00004101477],"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":[0.0004231109,0.0003983521,0.0007858641,0.00005151047,0.00001255348,0.0001439385,0.00001710277,0.00009751895,0.9954731,0.00004155903,0.00006653869,0.002488873],"study_design_scores_gemma":[0.0001700307,0.01008253,0.01720452,0.00002156634,0.0001305187,0.003225671,0.00009762356,0.002011935,0.9628823,0.0000582469,0.00409901,0.00001611333],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914666,0.002278507,0.004672041,0.00008442213,0.00003017885,0.0001132677,0.0002880442,0.0001213279,0.0009457045],"genre_scores_gemma":[0.9892439,0.001751756,0.005053526,0.00005863462,0.00001846295,0.0001157783,0.001096369,0.0000273389,0.002634254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001768407,"threshold_uncertainty_score":0.005275965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1030282610577521,"score_gpt":0.4329346755516833,"score_spread":0.3299064144939312,"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."}}