{"id":"W3016979500","doi":"10.1101/2020.04.14.040576","title":"Subtypes of functional connectivity associate robustly with ASD diagnosis","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal; Institut Universitaire en Santé Mentale de Québec; McGill University; Institut Universitaire de Gériatrie de Montréal; Montreal Neurological Institute and Hospital","funders":"Compute Canada","keywords":"Autism; Generalizability theory; Robustness (evolution); Subtyping; Dimensionality reduction; Cluster analysis; Genetic data; Autism spectrum disorder; Functional connectivity; Computer science; Psychology; Artificial intelligence; Biology; Machine learning; Neuroscience; Medicine; Developmental psychology; Genetics; Gene","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":[0.002135514,0.0003879749,0.0005614536,0.001074402,0.0004207274,0.0009239417,0.0004891691,0.0005695574,0.001545588],"category_scores_gemma":[0.01588595,0.000230548,0.0004103344,0.0005911647,0.0007490327,0.0005136002,0.00101592,0.0007860924,0.0003272441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003767778,"about_ca_system_score_gemma":0.0003185567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002518688,"about_ca_topic_score_gemma":0.003408983,"domain_scores_codex":[0.998153,0.0005481617,0.0001972263,0.0006813276,0.000315477,0.0001047916],"domain_scores_gemma":[0.991939,0.002108486,0.002959472,0.001844964,0.0008022458,0.0003458704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000585887,0.00007389877,0.9627122,0.00004985033,0.0004910447,0.0001990715,0.0006732774,0.0008672042,0.01948688,0.0005763621,0.0009664961,0.01331781],"study_design_scores_gemma":[0.00001407803,0.00007433572,0.991499,0.00001770395,0.000065451,0.0005513866,0.0002481705,0.002865128,0.002058236,0.002192881,0.0003950424,0.00001858223],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946853,0.00009347713,0.003566403,0.000107304,0.00001152402,0.00002124839,0.0009347392,0.00004546671,0.0005344907],"genre_scores_gemma":[0.9974161,0.00001768824,0.001549609,0.00002005809,0.000007589138,0.00002629645,0.0007699106,0.00002210039,0.0001706761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002518688,"threshold_uncertainty_score":0.01129383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03977924848111888,"score_gpt":0.2455911046974921,"score_spread":0.2058118562163732,"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."}}