{"id":"W4210411643","doi":"10.1016/j.neuroimage.2022.118965","title":"Anatomical variability, multi-modal coordinate systems, and precision targeting in the marmoset brain","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Primate Behavior and Ecology","field":"Psychology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rogue Research (Canada)","funders":"National Institute of Mental Health; Japan Society for the Promotion of Science; National Institutes of Health; Japan Agency for Medical Research and Development","keywords":"Marmoset; Neuroimaging; Callithrix; Neuroscience; Computer science; Coordinate system; Artificial intelligence; Computer vision; Psychology; Biology","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":[0.001712133,0.0002999424,0.0003943976,0.0006089949,0.0003982292,0.0005994638,0.0005206416,0.0003248887,0.000997341],"category_scores_gemma":[0.004569043,0.0002900668,0.0002719331,0.0004608026,0.0009063018,0.0005226267,0.001018979,0.0003927334,0.0001494053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003854465,"about_ca_system_score_gemma":0.0004093772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002282891,"about_ca_topic_score_gemma":0.003305395,"domain_scores_codex":[0.9989702,0.0002718656,0.00007780638,0.0002920232,0.0003166387,0.00007161601],"domain_scores_gemma":[0.998877,0.0002723047,0.0003718582,0.000284553,0.0001511213,0.00004312737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004603046,0.00006112942,0.04915783,0.0004783641,0.0004350693,0.0004244531,0.001602528,0.02407261,0.8048266,0.004432064,0.0005691907,0.1134798],"study_design_scores_gemma":[0.00002357737,0.0007470959,0.7903793,0.0000927185,0.0003203473,0.002324265,0.0004980423,0.05664667,0.1343822,0.009018635,0.005431464,0.0001357578],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8292175,0.001060848,0.1669019,0.0001585947,0.0000296161,0.00006156528,0.0003929616,0.0003832811,0.00179378],"genre_scores_gemma":[0.975807,0.000162466,0.02323598,0.00004646228,0.000009337824,0.00009396923,0.0002654752,0.000103241,0.0002761833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002282891,"threshold_uncertainty_score":0.00905472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03680711212608363,"score_gpt":0.3364451443487987,"score_spread":0.2996380322227151,"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."}}