{"id":"W4403207937","doi":"10.1162/imag_a_00331","title":"Assessing the consistency and sensitivity of the neural correlates of narrative stimuli using functional near-infrared spectroscopy","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canadian Institute for Advanced Research","keywords":"Functional near-infrared spectroscopy; Neural correlates of consciousness; Psychology; Narrative; Cognition; Cognitive psychology; Contrast (vision); Consistency (knowledge bases); Audiology; Brain activity and meditation; Electroencephalography; Neuroscience; Computer science; Artificial intelligence; Medicine; Prefrontal cortex","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":[0.001480354,0.00034347,0.0002592801,0.0007396275,0.000207988,0.0006666623,0.0002618338,0.0005124393,0.001390988],"category_scores_gemma":[0.008257923,0.0002391158,0.0001935761,0.0002601363,0.0004098453,0.0005403135,0.0005064455,0.0004554871,0.0002548125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001311398,"about_ca_system_score_gemma":0.0001049624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006578703,"about_ca_topic_score_gemma":0.001058964,"domain_scores_codex":[0.9993129,0.0001792822,0.00007701923,0.0001989624,0.00018281,0.00004894664],"domain_scores_gemma":[0.9967716,0.001633278,0.0008071362,0.0002541641,0.0004343268,0.00009942384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001977654,0.0002180501,0.1772681,0.000368599,0.0006367016,0.0003618188,0.001581387,0.002101433,0.7617651,0.0003906205,0.0003691557,0.05296145],"study_design_scores_gemma":[0.00003078329,0.0006122851,0.8983511,0.000044849,0.000128279,0.001097571,0.0009091342,0.006724537,0.09076655,0.0007910583,0.0005008335,0.00004296513],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911589,0.0001822978,0.00718553,0.00003883462,0.00001667824,0.00003697633,0.0001324178,0.00004601178,0.001202332],"genre_scores_gemma":[0.9958934,0.00004777313,0.003676516,0.00003114533,0.00001027648,0.00002443247,0.00008617784,0.00001527826,0.0002149935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001480354,"threshold_uncertainty_score":0.007828951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03748754815146491,"score_gpt":0.3585448863341838,"score_spread":0.3210573381827189,"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."}}