{"id":"W4367302277","doi":"10.1101/2023.04.27.537761","title":"LEVERAGING THE POWER OF 3D BRAIN-WIDE IMAGING AND MAPPING TOOLS FOR BRAIN INJURY RESEARCH IN MURINE MODELS","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; International Collaboration On Repair Discoveries; Vancouver Coastal Health","funders":"","keywords":"Traumatic brain injury; Brain atlas; Neuroimaging; Medicine; Neuroscience; Psychology","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":[0.002041397,0.001124345,0.0008544396,0.002973958,0.0005115816,0.002066526,0.001381011,0.001160471,0.004941503],"category_scores_gemma":[0.00118474,0.0009930431,0.001335856,0.0006472931,0.0009604229,0.001327087,0.002021751,0.002998662,0.001692658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004937118,"about_ca_system_score_gemma":0.0008661019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001166061,"about_ca_topic_score_gemma":0.002503381,"domain_scores_codex":[0.999089,0.0001540391,0.00006090045,0.0001671221,0.0004388087,0.00009016912],"domain_scores_gemma":[0.9988924,0.0002240292,0.0002348831,0.0002737773,0.0002215156,0.0001534065],"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":[0.000191108,0.0001066427,0.0009968571,0.0006122161,0.0001289395,0.0003530998,0.0001654462,0.007033452,0.9364469,0.008137845,0.004662508,0.041165],"study_design_scores_gemma":[0.0001064698,0.0007422436,0.01048216,0.0005283327,0.000290748,0.002745271,0.0002142678,0.05567717,0.8040067,0.01094245,0.1140254,0.0002386604],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05737602,0.002514826,0.9207903,0.000937351,0.0004177888,0.0003269722,0.004260485,0.008587629,0.004788655],"genre_scores_gemma":[0.240565,0.004824199,0.7362353,0.0005274233,0.0001699786,0.001642648,0.004111835,0.004592238,0.007331366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004941503,"threshold_uncertainty_score":0.01653093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04288207587712461,"score_gpt":0.3035371189840185,"score_spread":0.2606550431068939,"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."}}