{"id":"W3191819586","doi":"10.1016/j.schres.2021.07.032","title":"Everything is connected: Inference and attractors in delusions","year":2021,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Mental Health Research Topics","field":"Psychology","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"UCLH Biomedical Research Centre; Medical Research Council; Rosetrees Trust; Status of Women Canada; National Institute for Health and Care Research; Gatsby Charitable Foundation; Wellcome Trust","keywords":"Inference; Psychology; Bayesian inference; Certainty; Cognitive psychology; Bayes' theorem; Odds; Bayesian probability; Delusion; Schizophrenia (object-oriented programming); Frequentist probability; Artificial intelligence; Computer science; Machine learning; Mathematics; Psychiatry","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":[0.0008310854,0.0002559286,0.0003247385,0.0005073596,0.0005169114,0.001374817,0.0004352918,0.000803498,0.003142177],"category_scores_gemma":[0.008523553,0.0002950775,0.000683506,0.0002236653,0.002122822,0.001677206,0.001402968,0.001321958,0.0001343611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006923536,"about_ca_system_score_gemma":0.000313977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002960348,"about_ca_topic_score_gemma":0.001690524,"domain_scores_codex":[0.99968,0.0001605522,0.00001407611,0.00006151276,0.00004007658,0.00004382682],"domain_scores_gemma":[0.9964373,0.002437556,0.0004556827,0.0002736059,0.0001658854,0.0002299212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006522945,0.0001974243,0.03551714,0.000159036,0.0002710317,0.001071707,0.003228838,0.4703859,0.01279295,0.4328309,0.002858131,0.04003469],"study_design_scores_gemma":[0.00004447375,0.00007522575,0.005728165,0.00004304743,0.00003494308,0.0001353947,0.0003931283,0.5790125,0.0009510248,0.4128303,0.0007147104,0.0000371743],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8727872,0.0004666485,0.1120056,0.003947295,0.0000542862,0.00002607161,0.0002089634,0.0003000974,0.01020363],"genre_scores_gemma":[0.9953076,0.00007953383,0.004112815,0.00005493245,0.000006971327,0.0000110657,0.00003465504,0.00001245814,0.0003797572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003142177,"threshold_uncertainty_score":0.01051164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2421018166652103,"score_gpt":0.5356481524045718,"score_spread":0.2935463357393615,"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."}}