{"id":"W4386391777","doi":"10.1007/s10143-023-02129-7","title":"Whole-tumor histogram analysis of multi-parametric MRI for differentiating brain metastases histological subtypes in lung cancers: relationship with the Ki-67 proliferation index","year":2023,"lang":"en","type":"article","venue":"Neurosurgical Review","topic":"Lung Cancer Research Studies","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Natural Science Foundation of China","keywords":"Medicine; Kurtosis; Effective diffusion coefficient; Lung cancer; Percentile; Nuclear medicine; Skewness; Coefficient of variation; Adenocarcinoma; Standard deviation; Ki-67; Histogram; Radiology; Pathology; Cancer; Internal medicine; Magnetic resonance imaging; Immunohistochemistry; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001228592,0.0001917535,0.0009772291,0.0005098287,0.000131061,0.00002093254,0.000148896,0.00004501099,0.00003699648],"category_scores_gemma":[0.006811444,0.0001048025,0.00030583,0.005199698,0.0001879904,0.00006463248,0.00006671486,0.0003532988,0.000003614029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000301937,"about_ca_system_score_gemma":0.0001549314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007700225,"about_ca_topic_score_gemma":0.0003523984,"domain_scores_codex":[0.9975941,0.0004776988,0.0005877379,0.0004252577,0.0005720512,0.00034322],"domain_scores_gemma":[0.9961754,0.002904799,0.0002834409,0.0003384205,0.0002003887,0.00009751842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005752443,0.0003115478,0.9728234,0.007184916,0.0008891519,0.0001046881,0.0001688219,0.001794112,0.0001111438,0.0003550602,0.00907765,0.006604267],"study_design_scores_gemma":[0.001659259,0.0004387766,0.928198,0.001332761,0.002606431,0.000009108886,0.00003252033,0.03922219,0.00001388425,0.00001102083,0.02630634,0.0001696499],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7379943,0.1777412,0.00704409,0.06438758,0.0001822354,0.01191963,0.000236519,0.0003146317,0.0001798225],"genre_scores_gemma":[0.9914735,0.005808291,0.0002590264,0.0009180265,0.00002883039,0.001088569,0.000125851,0.00002064069,0.0002772644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2534792,"threshold_uncertainty_score":0.8154427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07793797974727316,"score_gpt":0.3945653936290378,"score_spread":0.3166274138817646,"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."}}