{"id":"W2043890552","doi":"10.1088/1751-8113/47/27/275301","title":"A Bayesian approach to compatibility, improvement, and pooling of quantum states","year":2014,"lang":"en","type":"article","venue":"Journal of Physics A Mathematical and Theoretical","topic":"Quantum Mechanics and Applications","field":"Physics and Astronomy","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Quantum state; Pooling; Computer science; Quantum; Quantum probability; Bayesian probability; Theoretical computer science; Mathematics; Quantum process; Artificial intelligence; Quantum mechanics; Quantum dynamics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01955671,0.001353347,0.001724433,0.002540819,0.002365761,0.003746368,0.004460627,0.003939492,0.004061673],"category_scores_gemma":[0.04938111,0.001426955,0.002082792,0.002923088,0.008732823,0.013765,0.006538165,0.005323349,0.0005631681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003014793,"about_ca_system_score_gemma":0.002703955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002650689,"about_ca_topic_score_gemma":0.001741802,"domain_scores_codex":[0.9851815,0.008452603,0.0006982095,0.002291368,0.002882627,0.0004938145],"domain_scores_gemma":[0.9744476,0.0165916,0.002536334,0.00357498,0.002196541,0.0006530427],"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":[0.0000651879,0.00004202481,0.0003905731,0.00007705773,0.00005101538,0.00004886116,0.0003153687,0.01829262,0.0007281861,0.9494514,0.0006433309,0.02989444],"study_design_scores_gemma":[0.00002097173,0.00005666207,0.0002221408,0.00002173527,0.00002531218,0.00003752421,0.0000253229,0.08716029,0.0006999503,0.9099061,0.001788996,0.00003501265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003948553,0.0001638883,0.9926858,0.0006787577,0.00002375288,0.0000580689,0.00004607927,0.00006849958,0.00232669],"genre_scores_gemma":[0.2756667,0.0004979693,0.7198822,0.0006491339,0.0004668581,0.0004082729,0.0001755402,0.0001117458,0.002141451],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01955671,"threshold_uncertainty_score":0.1034271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00841888955367249,"score_gpt":0.2456561549770142,"score_spread":0.2372372654233417,"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."}}