{"id":"W4414870063","doi":"10.1101/2025.10.05.680511","title":"Mixture Models for Domain-Adaptive Brain Decoding","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Decoding methods; Mixture model; Weighting; Scalability; Selection (genetic algorithm); Generalization; Inference; Model selection","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":[0.002311014,0.001069069,0.001030318,0.001003263,0.0003542457,0.001028134,0.001890966,0.00120803,0.002895286],"category_scores_gemma":[0.009064263,0.0006599359,0.001189947,0.0009215113,0.0009858368,0.001501988,0.002283148,0.002663707,0.001711634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001049443,"about_ca_system_score_gemma":0.0009878526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003570462,"about_ca_topic_score_gemma":0.003913535,"domain_scores_codex":[0.9990017,0.0004544368,0.00004715372,0.0002034747,0.0002169417,0.00007631],"domain_scores_gemma":[0.9981365,0.001184014,0.000113884,0.0002298475,0.0002763623,0.00005926646],"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":[0.0001610445,0.00007681056,0.0006268166,0.0001028159,0.000148876,0.000067604,0.0001402006,0.6802146,0.01181476,0.05598647,0.003798017,0.2468619],"study_design_scores_gemma":[0.000006033227,0.000008613787,0.00006933386,0.000004433925,0.00000512981,0.0000136276,0.00000390611,0.9797478,0.00144616,0.01804077,0.0006479974,0.0000060773],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002118969,0.00008429509,0.9970676,0.00008125744,0.00001172119,0.00001332262,0.00002842303,0.0003189101,0.0002754512],"genre_scores_gemma":[0.2414435,0.0003825,0.7510784,0.0003045196,0.0001124791,0.0002862115,0.0005478046,0.0007144507,0.005130124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003570462,"threshold_uncertainty_score":0.01222199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02739200906166949,"score_gpt":0.2393432915219917,"score_spread":0.2119512824603222,"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."}}