{"id":"W2285815731","doi":"10.1038/srep21768","title":"Exploring miniature insect brains using micro-CT scanning techniques","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Environment Research Council; Comisión Nacional de Investigación Científica y Tecnológica; Directorate for Biological Sciences; Imperial College London; Department for Environment, Food and Rural Affairs, UK Government; Biotechnology and Biological Sciences Research Council; W. Garfield Weston Foundation; Wellcome Trust; Leverhulme Trust; Corporación de Fomento de la Producción","keywords":"Bumblebee; Computer science; Bombus terrestris; Brain tissue; Insect; Brain function; Neuroimaging; 3D reconstruction; Protocol (science); Artificial intelligence; Computed tomography; Biology; Computer vision; Neuroscience; Ecology; Medicine; Pathology; Pollinator; Radiology; Pollination","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003056338,0.0004933975,0.0001515084,0.0009998773,0.0004634642,0.0005343495,0.0005042686,0.0005403694,0.005185106],"category_scores_gemma":[0.0003753062,0.0004524107,0.0002921913,0.0003797873,0.0004395883,0.0006875798,0.0004609647,0.0006826008,0.0006606659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002447769,"about_ca_system_score_gemma":0.000381007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001455515,"about_ca_topic_score_gemma":0.005270413,"domain_scores_codex":[0.9998764,0.00001517406,0.00001080148,0.0000364813,0.00004898812,0.00001214041],"domain_scores_gemma":[0.99976,0.00009979641,0.00004578107,0.00004259474,0.00003379244,0.00001807853],"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":[0.00006375465,0.00002392214,0.002835757,0.0002887629,0.00004675599,0.000470569,0.000180308,0.001574002,0.961539,0.0008453581,0.0003911441,0.0317406],"study_design_scores_gemma":[0.00006217588,0.001098761,0.1258584,0.0003335539,0.0003269152,0.02489927,0.001101816,0.02551931,0.7698638,0.003811285,0.04694458,0.0001802004],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5110208,0.006368013,0.46559,0.001036686,0.000103193,0.0006070539,0.002318215,0.001147823,0.01180816],"genre_scores_gemma":[0.4195229,0.004795197,0.5704744,0.0002116081,0.00005563857,0.0002979,0.0008907845,0.0001533803,0.00359812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005185106,"threshold_uncertainty_score":0.01734591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1805988440450433,"score_gpt":0.247658927007178,"score_spread":0.06706008296213462,"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."}}