{"id":"W2138194284","doi":"10.1016/j.jneumeth.2013.12.012","title":"There's more than one way to scan a cat: Imaging cat auditory cortex with high-field fMRI using continuous or sparse sampling","year":2014,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Auditory cortex; Inferior colliculus; Functional magnetic resonance imaging; Midbrain; Stimulus (psychology); Thalamus; Neuroscience; Voxel; Auditory system; Psychology; Computer science; Artificial intelligence; Central nervous system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002807006,0.0003394928,0.0006630081,0.0004533289,0.0006970447,0.0002560582,0.0008409844,0.0000534971,0.00001415338],"category_scores_gemma":[0.03110771,0.0002419651,0.0001270366,0.001144404,0.0004042765,0.0006859369,0.0002822223,0.000467793,0.000003592028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001968912,"about_ca_system_score_gemma":0.0003029486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001365773,"about_ca_topic_score_gemma":0.00003879677,"domain_scores_codex":[0.9958909,0.0009784159,0.000590167,0.0007855161,0.001097835,0.0006572106],"domain_scores_gemma":[0.990316,0.007761816,0.0007635481,0.0004853875,0.0003174339,0.0003558704],"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":[0.0002908282,0.0001213824,0.00194655,0.00001535374,0.000005918153,0.0001090045,0.0004248865,0.002173303,0.9851338,0.0001113027,0.0002290132,0.009438681],"study_design_scores_gemma":[0.002164621,0.004978685,0.187743,0.0007909755,0.0002283631,0.004817674,0.00163032,0.02557165,0.7582043,0.001152441,0.01132608,0.001391825],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7337516,0.00001626295,0.2563447,0.006494876,0.003030608,0.0002095031,0.000003705109,0.0000426302,0.0001061007],"genre_scores_gemma":[0.8218918,0.00001415628,0.1678518,0.009347996,0.0006907802,0.000006118828,4.240966e-8,0.00004279716,0.0001544879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2269294,"threshold_uncertainty_score":0.9867051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1071651241804222,"score_gpt":0.3786414858582133,"score_spread":0.2714763616777911,"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."}}