{"id":"W4288409740","doi":"10.5281/zenodo.5874920","title":"Semi-automated 3D segmentation of human skeletal muscle using Focused Ion Beam-Scanning Electron Microscopic images (CA1 Hippocampal Tissue)","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Hippocampal formation; Segmentation; Scanning electron microscope; Focused ion beam; Materials science; Biomedical engineering; Ion; Anatomy; Artificial intelligence; Computer science; Chemistry; Biology; Medicine; Neuroscience","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":[0.0005020424,0.001230371,0.0009967041,0.003366889,0.0006339771,0.001144357,0.00108326,0.001267671,0.005035774],"category_scores_gemma":[0.0006042787,0.0008296149,0.001362,0.001599575,0.0003818199,0.0003914629,0.001032667,0.0006823204,0.004749005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005678455,"about_ca_system_score_gemma":0.001422991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01439095,"about_ca_topic_score_gemma":0.04251809,"domain_scores_codex":[0.999637,0.00001967227,0.00003138527,0.0001554636,0.00009645738,0.00006008283],"domain_scores_gemma":[0.9996889,0.00005327815,0.00003263095,0.00008015475,0.0001188156,0.00002631272],"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":[0.001552184,0.000476468,0.01806687,0.004001562,0.001258869,0.001645563,0.0008941576,0.02684873,0.4392321,0.001840592,0.1700901,0.3340927],"study_design_scores_gemma":[0.0006088277,0.00073962,0.2258977,0.001169716,0.001166276,0.01087546,0.001336439,0.244748,0.3130906,0.008009685,0.191923,0.0004347419],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.384584,0.007194597,0.2338117,0.001017341,0.000487579,0.00139972,0.3112664,0.05046131,0.00977738],"genre_scores_gemma":[0.2855673,0.002440171,0.340441,0.0004648095,0.0001088536,0.0009041151,0.3546066,0.004796857,0.01067023],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01439095,"threshold_uncertainty_score":0.02861434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01617147019570289,"score_gpt":0.2752520644997921,"score_spread":0.2590805943040893,"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."}}