{"id":"W4417025391","doi":"10.1002/mds.70136","title":"Reply to: Deep Learning to Differentiate Parkinsonian Syndromes: From Proof of Concept to Clinical Trust","year":2025,"lang":"en","type":"article","venue":"Movement Disorders","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Chugiak-Eagle River Foundation; Agence Nationale de la Recherche","keywords":"Deep learning; Proof of concept; Deep brain stimulation; Parkinson's disease; Clinical neurology","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":[0.0005140518,0.0002432479,0.0004660908,0.0002544822,0.0001629297,0.000102686,0.001237016,0.00007971247,0.00009488195],"category_scores_gemma":[0.0007240254,0.0002430503,0.0001367313,0.000861362,0.00003614035,0.00009494338,0.0008749276,0.0003777957,0.00003774898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001023851,"about_ca_system_score_gemma":0.000088844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002587716,"about_ca_topic_score_gemma":0.0006603005,"domain_scores_codex":[0.9969478,0.0003693577,0.0008114618,0.0009249696,0.0004470139,0.0004994299],"domain_scores_gemma":[0.9981679,0.0002993083,0.000168891,0.0009544086,0.0000952859,0.000314152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000054102,0.0002463379,0.5113386,0.00007292727,0.00009904431,0.000004728404,0.005710591,0.01655601,0.00002706326,0.002099384,0.004531109,0.4592601],"study_design_scores_gemma":[0.001303865,0.001885504,0.8541493,0.0005646963,0.00002916023,8.8922e-8,0.001132276,0.04986547,0.0005512458,0.01012841,0.07972125,0.0006687511],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4771498,0.000173753,0.4768325,0.04244957,0.001086736,0.001250429,0.000009267525,0.0001953069,0.0008526278],"genre_scores_gemma":[0.9499837,0.00001211726,0.01561602,0.03310702,0.00004020519,0.0001385169,0.00001001161,0.00002129849,0.001071094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4728339,"threshold_uncertainty_score":0.9911304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893365976594162,"score_gpt":0.3240092611351107,"score_spread":0.3050756013691691,"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."}}