{"id":"W4413273653","doi":"10.1162/imag.a.136","title":"The lab streaming layer for synchronized multimodal recording","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Subtitles and Audiovisual Media","field":"Arts and Humanities","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital","funders":"Army Research Laboratory; National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; University of California, San Diego","keywords":"Layer (electronics); Computer science; Streaming current; Application layer; Multimedia; Nanotechnology; Materials science; Operating system","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":[0.001984173,0.001075823,0.0006697921,0.001337749,0.0005477494,0.002199111,0.002658877,0.0008883757,0.03293312],"category_scores_gemma":[0.004515165,0.0005795703,0.0005526756,0.0007336917,0.0006364554,0.003047694,0.003666616,0.001484,0.01178015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001193551,"about_ca_system_score_gemma":0.001658027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001547627,"about_ca_topic_score_gemma":0.001490014,"domain_scores_codex":[0.9985562,0.0001657741,0.0001313784,0.0002639749,0.0007280091,0.0001545753],"domain_scores_gemma":[0.9977896,0.0004258634,0.0001818582,0.0005576618,0.0007853369,0.0002596997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001870087,0.0003968264,0.004289245,0.001261401,0.0001934922,0.00105674,0.0008724624,0.007819736,0.350902,0.04184024,0.1594025,0.4300953],"study_design_scores_gemma":[0.0003140361,0.0007516757,0.003895299,0.0004964346,0.0001734302,0.001471673,0.0002758588,0.2068797,0.2852542,0.02316355,0.4769081,0.0004160223],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0156206,0.0008426568,0.853911,0.001099523,0.000590637,0.0009494922,0.003001159,0.09734815,0.02663676],"genre_scores_gemma":[0.3015527,0.001882494,0.630851,0.003156618,0.0008583394,0.003230614,0.01103286,0.009618167,0.03781721],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03293312,"threshold_uncertainty_score":0.1101723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03372978604898877,"score_gpt":0.2992186334716934,"score_spread":0.2654888474227046,"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."}}