{"id":"W4399995627","doi":"10.1162/imag_a_00222","title":"Challenges in multi-task learning for fMRI-based diagnosis: Benefits for psychiatric conditions and CNVs would likely require thousands of patients","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; Institut universitaire en santé mentale de Montréal; Institut Universitaire en Santé Mentale de Québec; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"National Institute of Mental Health; Compute Canada; Canadian Institutes of Health Research; National Institutes of Health; Canada First Research Excellence Fund; Simons Foundation Autism Research Initiative; Health and Care Research Wales; Courtois Foundation; Consortium canadien en neurodégénérescence associée au vieillissement; Wellcome Trust; Institut de Valorisation des Données; Fondation Brain Canada","keywords":"Task (project management); Psychology; Psychiatry; Cognitive psychology; Clinical psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01955234,0.002006905,0.002931191,0.0009857157,0.001662164,0.002149503,0.003122933,0.003628428,0.004572384],"category_scores_gemma":[0.04788328,0.0009142224,0.001748035,0.001551419,0.001837623,0.003514792,0.003879526,0.004996945,0.00427065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001395635,"about_ca_system_score_gemma":0.002167367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006475314,"about_ca_topic_score_gemma":0.008002309,"domain_scores_codex":[0.9914117,0.005560108,0.0004053191,0.001620021,0.0007260187,0.0002768274],"domain_scores_gemma":[0.9604407,0.02853849,0.00113795,0.005583239,0.00276794,0.001531689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006246784,0.00260758,0.06713362,0.001520728,0.0018958,0.001074057,0.0009597708,0.2051772,0.01573607,0.007285721,0.04322764,0.647135],"study_design_scores_gemma":[0.0005178701,0.001331473,0.02027684,0.0001800411,0.0002104813,0.0009104346,0.0006339893,0.9006687,0.005494543,0.05936322,0.01027562,0.0001367847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3750937,0.01574354,0.555989,0.03053602,0.001582612,0.00101906,0.004882629,0.007392345,0.007761138],"genre_scores_gemma":[0.7621074,0.001637361,0.2226214,0.003451316,0.0008160481,0.0008785987,0.004792128,0.0003868805,0.003308915],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01955234,"threshold_uncertainty_score":0.1034039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1064990478113235,"score_gpt":0.3360904326541408,"score_spread":0.2295913848428173,"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."}}