{"id":"W4394039702","doi":"10.5281/zenodo.4778711","title":"Maximally Predictive Ensemble Dynamics from Data","year":2021,"lang":"en","type":"dataset","venue":"VU Research Portal","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute","funders":"","keywords":"Dynamics (music); Computer science; Physics","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0007434758,0.0002359759,0.0003015457,0.0001845457,0.0003063931,0.0006577818,0.006866716,0.0002574305,0.0003152596],"category_scores_gemma":[0.0001846836,0.000223461,0.00006757757,0.0009995303,0.0001622667,0.0004579561,0.007193648,0.0015208,0.0003457257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005966854,"about_ca_system_score_gemma":0.000798436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001765982,"about_ca_topic_score_gemma":0.003823365,"domain_scores_codex":[0.9959198,0.0002289269,0.0003364495,0.001448861,0.001376026,0.0006899198],"domain_scores_gemma":[0.9933615,0.0004817008,0.0001197281,0.005432815,0.0003222428,0.0002819875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003549918,0.0001050754,0.000004709104,0.00001308866,0.00004937407,0.0006020447,0.000004213041,0.00001016917,0.000007346601,0.001080131,0.9942786,0.003841756],"study_design_scores_gemma":[0.00009677755,0.00005515772,0.00007043151,0.00006342907,0.00001217923,0.00002101631,0.00002029603,0.04658411,0.000009788387,0.001332339,0.9515215,0.0002130326],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000194412,0.0003410563,0.01509791,0.0009811949,0.0003409577,0.0003600241,0.9815663,0.00006463013,0.001228505],"genre_scores_gemma":[0.0001347434,0.001121733,0.003224631,0.000104179,0.0006696802,0.00008462554,0.9942682,0.00001716474,0.0003749757],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04657394,"threshold_uncertainty_score":0.9985066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1097553022455365,"score_gpt":0.3848391323224565,"score_spread":0.2750838300769199,"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."}}