{"id":"W4402437891","doi":"10.1038/s41586-024-07939-3","title":"Connectome-constrained networks predict neural activity across the fly visual system","year":2024,"lang":"en","type":"article","venue":"Nature","topic":"Neurobiology and Insect Physiology Research","field":"Neuroscience","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital","funders":"Bundesministerium für Bildung und Forschung; European Commission; International Max Planck Research School for Environmental, Cellular and Molecular Microbiology; Deutsche Forschungsgemeinschaft; Howard Hughes Medical Institute","keywords":"Connectome; Artificial neural network; Computer science; Artificial intelligence; Models of neural computation; Biological neural network; Neuron; Feature (linguistics); Neuroscience; Biological system; Functional connectivity; Machine learning; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0003825268,0.0001880798,0.0001917761,0.0000438041,0.00051295,0.0001356192,0.0005146657,0.001035502,0.00004154078],"category_scores_gemma":[0.0003442955,0.0001110065,0.0001235566,0.0005269962,0.0006407177,0.0001907715,0.0001964718,0.005875812,0.00007396089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003416918,"about_ca_system_score_gemma":0.0000665732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000381614,"about_ca_topic_score_gemma":0.000003835839,"domain_scores_codex":[0.9979031,0.0006100535,0.0001292292,0.0005857344,0.0001926491,0.000579217],"domain_scores_gemma":[0.9981049,0.001461531,0.0000343213,0.0002933218,0.00003251528,0.0000734178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003717423,0.00006150818,0.000314012,0.0001156125,0.00003565329,0.0004118122,0.0002096383,0.0002831522,0.9814367,0.006070575,0.006024632,0.004665019],"study_design_scores_gemma":[0.001338756,0.001258607,0.03254804,0.0002219215,0.00005399707,0.002303694,0.0002972689,0.506429,0.4444191,0.0003081673,0.01003411,0.0007873655],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934915,0.0004813692,0.00003556642,0.001348729,0.002679775,0.0003426544,0.00007497105,0.0004180801,0.001127323],"genre_scores_gemma":[0.9973881,0.00002062597,7.572653e-7,0.001534293,0.0005951372,0.00003529687,0.00000511465,0.00002095808,0.0003997346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5370175,"threshold_uncertainty_score":0.9964177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01601444182494423,"score_gpt":0.3344000171860626,"score_spread":0.3183855753611184,"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."}}