{"id":"W7098116954","doi":"","title":"NEPTSim: Simulating NEPTUNE Canada using OMNeT++","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004300731,0.0000846129,0.00006608885,0.000008083796,0.00009714905,0.000009091017,0.00009572147,0.00004594609,0.00002351854],"category_scores_gemma":[0.00001819424,0.00008247021,0.00002168016,0.00005453347,0.00001864989,0.00000141104,0.00004647156,0.0000464675,9.725875e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003327948,"about_ca_system_score_gemma":0.0001268218,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03990076,"about_ca_topic_score_gemma":0.07086803,"domain_scores_codex":[0.9994511,0.00001147031,0.0001077947,0.0001903466,0.00005025602,0.0001890042],"domain_scores_gemma":[0.9996463,0.000006328371,0.00003922238,0.000225581,0.00003462277,0.00004793215],"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":[0.000002613191,0.000004271669,0.0002406578,0.000002005368,0.000003943959,8.677586e-8,0.000001071321,0.003531684,0.991243,0.0007159589,0.002169178,0.002085538],"study_design_scores_gemma":[0.00009793507,0.00004215661,0.00005190584,0.000002723705,0.000004377373,0.00000367859,0.00001023217,0.01120665,0.6876925,0.0002039661,0.3005386,0.0001452373],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4608926,0.00006529158,0.5343388,0.00008681037,0.00002586181,0.0001030694,0.000003674535,0.00002712079,0.004456821],"genre_scores_gemma":[0.9623858,0.000007711948,0.03557434,0.0009086884,0.0001222066,0.000006318573,0.00003758322,0.00001593661,0.0009413784],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5014933,"threshold_uncertainty_score":0.9664926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006903279087935032,"score_gpt":0.2989952841613837,"score_spread":0.2920920050734487,"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."}}