{"id":"W4383988325","doi":"10.48550/arxiv.2307.04256","title":"Framework for Learning and Control in the Classical and Quantum Domains","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Government of Alberta","keywords":"Computer science; Formalism (music); Quantum; Construct (python library); Control (management); Unification; Artificial intelligence; Physics; Quantum mechanics","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":[0.002150835,0.0009040879,0.0008971274,0.00138204,0.001199947,0.003289807,0.002367193,0.002521345,0.007859986],"category_scores_gemma":[0.002247136,0.0003810742,0.001396634,0.001224426,0.00652748,0.005035511,0.002433718,0.003753553,0.00115098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002294903,"about_ca_system_score_gemma":0.002258478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003515948,"about_ca_topic_score_gemma":0.002718135,"domain_scores_codex":[0.9990251,0.0004349888,0.00006280637,0.0001933684,0.0002008821,0.00008286007],"domain_scores_gemma":[0.9988436,0.0006033588,0.0001054914,0.0001895726,0.0001562511,0.0001017433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000002210449,0.000003779579,0.00001308551,0.00001455991,0.000002403354,0.00001180888,0.00002348927,0.0038448,0.00008459132,0.9946728,0.000256084,0.001070312],"study_design_scores_gemma":[0.000009724595,0.00000910576,0.00002420605,0.00001970582,0.000004232989,0.000017602,0.00001907988,0.0388634,0.00007818349,0.9543635,0.006584395,0.000006843713],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002295542,0.001247543,0.9666156,0.004660062,0.000175384,0.00006053108,0.0002312147,0.0001571451,0.02455698],"genre_scores_gemma":[0.3220657,0.00376383,0.6542997,0.001839432,0.0008975713,0.0009764299,0.0003826166,0.000168129,0.01560668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007859986,"threshold_uncertainty_score":0.02629423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0812077322536421,"score_gpt":0.2251763106103161,"score_spread":0.143968578356674,"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."}}