{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005870266,0.0001381691,0.0001586658,0.00002824049,0.0006621067,0.0001811278,0.000135205,0.00002880702,0.00007824855],"category_scores_gemma":[0.0001004428,0.00004189274,0.00009605985,0.0003971611,0.0001498602,0.0003522251,0.0001275837,0.0000601807,0.00001163757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003622873,"about_ca_system_score_gemma":0.00001286066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008326746,"about_ca_topic_score_gemma":0.0002793086,"domain_scores_codex":[0.9985657,0.00002622299,0.0002537584,0.0005397132,0.0002621925,0.0003524385],"domain_scores_gemma":[0.99957,0.00006380038,0.0001560979,0.0000608318,0.00006972255,0.00007959748],"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":[0.000002965956,0.00001314012,0.02255702,0.000002444783,0.00000530837,0.0001782569,0.00005196183,5.875672e-8,0.9469895,0.000006366857,0.001953634,0.02823932],"study_design_scores_gemma":[0.00002956856,0.00004650856,0.07164876,0.0002283449,0.000009936105,0.0004441321,0.0001670202,0.000001548416,0.6990417,0.0006619393,0.2274245,0.0002961005],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973451,0.0001855732,0.000002488671,0.00035854,0.0009421642,0.0001162818,0.000009612935,0.0001628575,0.0008773808],"genre_scores_gemma":[0.9981444,0.00002762151,0.00033117,0.00003442509,0.0002848934,0.00001195687,0.000006429023,0.000001154426,0.001157919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2479479,"threshold_uncertainty_score":0.5092456,"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."}}