{"id":"W4380369756","doi":"10.1093/neuonc/noad073.271","title":"MDB-39. ASSESSMENT OF MEDULLOBLASTOMA PATIENTS THROUGH MONITORING EXTRACELLULAR VESICLES VIA SURFACE-ENHANCED RAMAN SPECTROSCOPY COMBINED WITH MACHINE LEARNING","year":2023,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University","funders":"","keywords":"Extracellular vesicles; Liquid biopsy; Medulloblastoma; Machine learning; Computer science; Raman spectroscopy; Extracellular vesicle; Artificial intelligence; Medicine; Bioinformatics; Biomedical engineering; Pathology; Cancer; Chemistry; Internal medicine; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":{"n_in":0,"stratum":"aff_core","weight":5595.2375,"opus":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"Conference abstract on monitoring medulloblastoma via Raman spectroscopy of extracellular vesicles; a clinical biomarker question."},"gpt":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"It develops a cancer-monitoring assay using extracellular vesicles and machine learning, not research practice."},"grok":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"Biomedical liquid-biopsy diagnostic study of medulloblastoma, not metaresearch."}},"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003521112,0.0003500184,0.0003030127,0.0005945196,0.00016001,0.0003217508,0.0002150542,0.0002956421,0.0006144696],"category_scores_gemma":[0.0005303907,0.0001449874,0.0003498409,0.0002969395,0.0001139486,0.000168547,0.0002185517,0.0002331899,0.0002323822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002950826,"about_ca_system_score_gemma":0.0002146625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001878373,"about_ca_topic_score_gemma":0.00208892,"domain_scores_codex":[0.9997434,0.0000421962,0.00001764906,0.00009113067,0.00008260496,0.00002297807],"domain_scores_gemma":[0.9998589,0.00003638671,0.00004607865,0.00001028651,0.00003501603,0.00001326985],"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":[0.001604132,0.0002968752,0.1378722,0.0003182738,0.0002108798,0.0004561415,0.0001307518,0.01810702,0.7547529,0.0002844099,0.000973053,0.08499342],"study_design_scores_gemma":[0.00003907145,0.0009200024,0.1872647,0.0000427562,0.000163887,0.001105247,0.0001517411,0.1472118,0.6584873,0.0005065983,0.004042699,0.00006414679],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813462,0.001176361,0.01449567,0.00009974561,0.00002119217,0.00005945107,0.00174887,0.0002746744,0.0007780099],"genre_scores_gemma":[0.982114,0.0003205391,0.01530355,0.00004063486,0.000006419235,0.00006261095,0.00140294,0.00002687635,0.0007224309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001878373,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01094468508311616,"score_gpt":0.287793572053417,"score_spread":0.2768488869703009,"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."}}