{"id":"W4401609355","doi":"10.1038/s41386-024-01962-8","title":"Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction","year":2024,"lang":"en","type":"review","venue":"Neuropsychopharmacology","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trinity College","funders":"Trinity College Dublin; Yale University","keywords":"Connectomics; Connectome; Functional magnetic resonance imaging; Functional connectivity; Neuroimaging; Neuroscience; Conceptualization; Computer science; Functional neuroimaging; Psychology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004661986,0.001993432,0.004268241,0.003611939,0.0002594453,0.00205336,0.002196585,0.001578343,0.002164834],"category_scores_gemma":[0.007867672,0.0005895649,0.00106588,0.003540175,0.001698688,0.00183672,0.0008990857,0.001739124,0.001023236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008367534,"about_ca_system_score_gemma":0.001312156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001969985,"about_ca_topic_score_gemma":0.003219234,"domain_scores_codex":[0.9990199,0.0002252881,0.00008531436,0.0004009451,0.0002332391,0.00003546728],"domain_scores_gemma":[0.9935701,0.004690355,0.0005673086,0.000420141,0.0006572613,0.00009481044],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002799902,0.00007199258,0.004313952,0.01271999,0.001311585,0.000135802,0.00007210732,0.001109504,0.005066141,0.005465514,0.006898887,0.9625546],"study_design_scores_gemma":[0.0002958305,0.001366269,0.1016145,0.02986027,0.009693744,0.01151979,0.0006758033,0.009917683,0.0301984,0.1139205,0.6900719,0.0008653348],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001347787,0.9915578,0.004710283,0.0005093362,0.0001814907,0.00002279354,0.0003855882,0.00003949858,0.001245336],"genre_scores_gemma":[0.01528486,0.9751194,0.00711468,0.0005160604,0.0005384968,0.0001042362,0.0005514812,0.00002800413,0.0007427721],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.995338,"threshold_uncertainty_score":0.02465528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1386573848735271,"score_gpt":0.4241386047477808,"score_spread":0.2854812198742537,"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."}}