{"id":"W4395001742","doi":"10.21037/qims-23-1778","title":"A nomogram based on neuron-specific enolase and substantia nigra hyperechogenicity for identifying cognitive impairment in Parkinson’s disease","year":2024,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Enolase; Substantia nigra; Nomogram; Parkinson's disease; Neuroimaging; Disease; Medicine; Cognitive impairment; Biomarker; Cognition; Neuroscience; Internal medicine; Oncology; Pathology; Psychology; Psychiatry; Biology; Immunohistochemistry; Biochemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005935932,0.001701288,0.001196368,0.008338451,0.0009552171,0.002127323,0.001078763,0.001294794,0.001151266],"category_scores_gemma":[0.01414595,0.000341904,0.00143769,0.001881624,0.000846287,0.001734888,0.001281831,0.001103307,0.0007555305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009771921,"about_ca_system_score_gemma":0.001195385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003212183,"about_ca_topic_score_gemma":0.003849502,"domain_scores_codex":[0.9984239,0.0006368469,0.0001927008,0.0002781112,0.0003347519,0.0001335805],"domain_scores_gemma":[0.9918115,0.003598485,0.001449645,0.0003942153,0.001992712,0.0007533809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00122513,0.0001680775,0.9200542,0.0001621226,0.0003331514,0.000416366,0.0002119541,0.01406835,0.001070886,0.0004630257,0.004207508,0.05761939],"study_design_scores_gemma":[0.000289898,0.001581353,0.5443462,0.0003753091,0.001052766,0.003275379,0.001658733,0.42775,0.002944348,0.003498924,0.01294297,0.0002841397],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9097379,0.006183639,0.07195411,0.001400941,0.0004219154,0.0005341331,0.003356295,0.001239646,0.005171371],"genre_scores_gemma":[0.9699616,0.000893425,0.02655328,0.0001053321,0.0001148109,0.0002441438,0.001665514,0.00004941781,0.0004125455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008338451,"threshold_uncertainty_score":0.03139263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07944451162879268,"score_gpt":0.35078717075426,"score_spread":0.2713426591254673,"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."}}