{"id":"W7117292751","doi":"10.64898/2025.12.25.696483","title":"Hierarchical Semi-Markov Smooth Models of Latent Neural States","year":2025,"lang":"","type":"article","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Inference; Bayesian probability; Bayes' theorem; Latent variable; Covariate; Markov process; Bayesian inference; Latent variable model; Markov model","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003205279,0.0007721735,0.001279646,0.0009856204,0.000479093,0.001541679,0.002417911,0.001745407,0.00445716],"category_scores_gemma":[0.007822637,0.0009610613,0.002311456,0.000913535,0.001339187,0.001773452,0.00142814,0.00236475,0.001057339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482977,"about_ca_system_score_gemma":0.00147109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0107526,"about_ca_topic_score_gemma":0.01783369,"domain_scores_codex":[0.9988335,0.0005249272,0.00005959564,0.0003166376,0.0001275932,0.0001376279],"domain_scores_gemma":[0.9953419,0.003499791,0.0004062797,0.0003926819,0.0002235823,0.0001357855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000304846,0.00009962537,0.004323884,0.0001809185,0.0002082125,0.0001745884,0.0004306827,0.7547435,0.003632339,0.2025538,0.002295705,0.03105197],"study_design_scores_gemma":[0.00001390995,0.00001387402,0.0004824791,0.00001188831,0.0000133567,0.0000144737,0.000008782178,0.9524311,0.0002020654,0.04636027,0.0004353042,0.00001251672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0503303,0.0004146654,0.9455698,0.000454415,0.00004553724,0.00008026146,0.001070272,0.0008493966,0.00118537],"genre_scores_gemma":[0.7986048,0.0008086053,0.1859543,0.0003383552,0.0001361554,0.0007981414,0.003390437,0.0003141931,0.00965503],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0107526,"threshold_uncertainty_score":0.02138001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01984728377548418,"score_gpt":0.2309875665574895,"score_spread":0.2111402827820053,"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."}}