{"id":"W2008315227","doi":"10.1002/bip.10487","title":"Distinguishing and grading human gliomas by IR spectroscopy","year":2003,"lang":"en","type":"article","venue":"Biopolymers","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Institute for Biodiagnostics","funders":"","keywords":"Brain tissue; Astrocytoma; Grading (engineering); Chemistry; Glioma; Malignancy; Glioblastoma; Pathology; Spectroscopy; Infrared spectroscopy; Brain tumor; In vivo magnetic resonance spectroscopy; Biomedical engineering; Biology; Cancer research; Medicine; Radiology; Magnetic resonance imaging","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":[0.0003974271,0.0002800932,0.0001652299,0.001029997,0.0001261547,0.0002581681,0.0001204422,0.0002772567,0.0003956148],"category_scores_gemma":[0.0006035788,0.00009061262,0.0001301477,0.0003096992,0.000176071,0.0002093764,0.0001575663,0.0001741633,0.0003219972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001112156,"about_ca_system_score_gemma":0.0001156844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001204388,"about_ca_topic_score_gemma":0.001142482,"domain_scores_codex":[0.9998354,0.00003765112,0.00001380373,0.0000276226,0.00006048095,0.00002511361],"domain_scores_gemma":[0.9998569,0.00003300512,0.00003580025,0.000017197,0.00004160664,0.0000155091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005664182,0.00005603613,0.01954888,0.00009172531,0.00002504096,0.0001485162,0.0001173354,0.001156856,0.9340574,0.000189067,0.00013195,0.04391069],"study_design_scores_gemma":[0.00003819423,0.001611919,0.2477677,0.00004211639,0.0002066191,0.002937511,0.0004734025,0.02228502,0.7173054,0.001827006,0.005439917,0.00006523619],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977535,0.0007064564,0.0197498,0.00003502609,0.00001160722,0.00005741229,0.0001746058,0.0001744327,0.001555602],"genre_scores_gemma":[0.9742616,0.0006859291,0.02360644,0.00001557562,0.000004978449,0.00001986886,0.0004349835,0.00001718629,0.0009534388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001204388,"threshold_uncertainty_score":0.002394736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00790200268324676,"score_gpt":0.3022332675720191,"score_spread":0.2943312648887723,"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."}}