{"id":"W4399257125","doi":"10.1038/s41467-024-48747-7","title":"A 3D ray traced biological neural network learning model","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Defense Threat Reduction Agency; Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Government of Canada; U.S. Department of Defense","keywords":"Computer science; Artificial neural network; Computational biology; Artificial intelligence; Biology","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":[0.00042106,0.0006497533,0.000445381,0.000717203,0.0004885037,0.001173932,0.002385036,0.001888683,0.005577134],"category_scores_gemma":[0.001307754,0.0005497288,0.0009220848,0.0008747047,0.000756297,0.001044112,0.001094069,0.00137747,0.001440375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001445282,"about_ca_system_score_gemma":0.001261942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01804982,"about_ca_topic_score_gemma":0.01205595,"domain_scores_codex":[0.9998158,0.00003084326,0.000007325973,0.00006665335,0.00005984051,0.00001963252],"domain_scores_gemma":[0.9997212,0.00009649854,0.00003135091,0.0000344934,0.00009266662,0.00002366531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003056277,0.00001809088,0.0005400534,0.00002590368,0.00002031989,0.00006780854,0.00003110117,0.9661337,0.001413088,0.008933204,0.001579263,0.02120699],"study_design_scores_gemma":[0.000002701777,0.000005030899,0.00005008813,0.000003365442,0.000002223407,0.00001398103,0.000001982294,0.9965854,0.0002074087,0.002273651,0.0008507847,0.000003446427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01528042,0.0004047728,0.97243,0.0007750872,0.0001367665,0.00007095131,0.0006759064,0.001350404,0.008875688],"genre_scores_gemma":[0.4886034,0.001084182,0.477586,0.0007315901,0.0001229997,0.0006372814,0.001589376,0.0003857531,0.02925926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01804982,"threshold_uncertainty_score":0.03588951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03604522261591197,"score_gpt":0.3163668149784933,"score_spread":0.2803215923625813,"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."}}