{"id":"W4412166834","doi":"10.1017/cjn.2025.10287","title":"P.139 Predicting pituitary gland location during endoscopic endonasal surgery using machine learning model","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Pituitary gland; Computer science; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002962736,0.0002885192,0.0005072237,0.001466163,0.002406626,0.0005069321,0.0009993247,0.0001403566,0.00004651261],"category_scores_gemma":[0.002373856,0.0002167561,0.0002047342,0.001764044,0.002097107,0.0008275582,0.00004930756,0.001446978,8.479383e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002649555,"about_ca_system_score_gemma":0.002038714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001479059,"about_ca_topic_score_gemma":0.01255614,"domain_scores_codex":[0.9965773,0.0004857586,0.0008815809,0.0003644955,0.0005719499,0.00111892],"domain_scores_gemma":[0.9976405,0.0006029422,0.0003261521,0.0001039667,0.00025257,0.001073878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004620478,0.000005411879,0.6339425,0.00001919129,0.00001694046,0.000709996,0.00008321234,0.3639753,0.000190934,0.00003405471,0.00005600571,0.0009617499],"study_design_scores_gemma":[0.000208215,0.001267945,0.03956705,0.0001653647,0.00007554951,0.003252909,0.000113015,0.9518501,0.0003628743,0.002678989,0.0002067747,0.0002512798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928633,0.003174376,0.001523161,0.0007592549,0.0008030115,0.00005995384,0.000005314136,0.0000546485,0.0007570002],"genre_scores_gemma":[0.9969735,0.0005100299,0.001733088,0.0005492122,0.0001919886,0.000001253745,5.112565e-7,0.00001165829,0.00002877714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5943756,"threshold_uncertainty_score":0.9988921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02420212732615306,"score_gpt":0.2431441624103125,"score_spread":0.2189420350841594,"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."}}