{"id":"W3159267549","doi":"10.22331/q-2022-05-30-727","title":"Quantum Machine Learning with SQUID","year":2022,"lang":"en","type":"article","venue":"Quantum","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Pacific Northwest National Laboratory; Office of Science; University of Washington; Washington Research Foundation; Battelle; Laboratory Directed Research and Development; U.S. Department of Energy","keywords":"MNIST database; Quantum; Scalability; Squid; Variety (cybernetics); Binary number; Quantum computer; Quantum algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.0005055348,0.0002336581,0.0002397016,0.0001752048,0.001083857,0.0001497755,0.001221524,0.00002793757,0.0001034164],"category_scores_gemma":[0.00002486935,0.0001921141,0.00008746966,0.0007787048,0.00005325097,0.0001502335,0.000902888,0.0008399163,0.00004402461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005230519,"about_ca_system_score_gemma":0.0001011902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001167464,"about_ca_topic_score_gemma":0.000004768841,"domain_scores_codex":[0.9977545,0.0002573383,0.000234839,0.000598497,0.0006237148,0.0005310679],"domain_scores_gemma":[0.9989677,0.0001294357,0.0001445899,0.0005853747,0.00004164073,0.000131248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001513582,0.0005793824,0.00466554,0.00006661719,0.0001408955,0.001110508,0.005836926,0.3665093,0.001654145,0.5381072,0.003627826,0.07755025],"study_design_scores_gemma":[0.0003998184,0.000972713,0.0004483321,0.00001071187,0.000005328357,0.0003299489,0.00007853475,0.9275355,0.00008962798,0.003638537,0.06617874,0.0003122573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5240277,0.0009880633,0.4661967,0.004521754,0.001247487,0.0002893103,0.0000130567,0.001416849,0.001299061],"genre_scores_gemma":[0.9896675,0.00000628009,0.009217899,0.0004984403,0.0001066467,0.00002842661,0.0000118997,0.00003214525,0.0004307653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5610261,"threshold_uncertainty_score":0.8336266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008859587795351396,"score_gpt":0.2129566588955208,"score_spread":0.2040970711001694,"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."}}