{"id":"W4390619391","doi":"10.7554/elife.92200.1.sa1","title":"eLife Assessment: Comparative neuroimaging of sex differences in human and mouse brain anatomy","year":2024,"lang":"en","type":"peer-review","venue":"","topic":"Neuroendocrine regulation and behavior","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Compute Canada","keywords":"Neuroimaging; Human brain; Brain size; Stria terminalis; Neuroscience; Biology; Amygdala; Psychology; Brain morphometry; Anterior cingulate cortex; Sex characteristics; Cingulate cortex; Magnetic resonance imaging; Medicine; Central nervous system; Cognition; Endocrinology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003222637,0.001102064,0.001127989,0.003316564,0.001486248,0.002433483,0.002134875,0.003610908,0.05415758],"category_scores_gemma":[0.003188385,0.001685502,0.00133176,0.001166699,0.001590484,0.001690328,0.002484505,0.003120418,0.01310086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008147516,"about_ca_system_score_gemma":0.001500389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001842218,"about_ca_topic_score_gemma":0.005690527,"domain_scores_codex":[0.9978217,0.0002708038,0.0001383706,0.0006531927,0.0008025222,0.0003134918],"domain_scores_gemma":[0.997986,0.0003796552,0.0003562987,0.0004450944,0.0004636387,0.0003693891],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003579198,0.0004253951,0.01290512,0.001659825,0.0005593484,0.002288538,0.001268811,0.003198576,0.6368155,0.03248566,0.08917684,0.2156372],"study_design_scores_gemma":[0.001210839,0.001084219,0.07329696,0.001099578,0.0007284591,0.006826242,0.001030982,0.0280637,0.4884531,0.02070717,0.377213,0.0002857956],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2384012,0.004887918,0.5586828,0.009669084,0.003024871,0.0009682255,0.04184972,0.03926307,0.1032531],"genre_scores_gemma":[0.313371,0.003243565,0.5321701,0.003267595,0.0004645033,0.003927473,0.01807754,0.01380334,0.1116748],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9967774,"threshold_uncertainty_score":0.1811752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.11382994278784,"score_gpt":0.4732116242694508,"score_spread":0.3593816814816108,"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."}}