{"id":"W6948353456","doi":"10.48660/16120021","title":"Capturing Topological and Symmetry Protected Physics with Entanglement and Tensor Networks","year":2016,"lang":"en","type":"other","venue":"PIRSA","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Quantum entanglement; Symmetry (geometry); Tensor (intrinsic definition); Topology (electrical circuits); Tensor product","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004273458,0.0002241477,0.0002484109,0.00002955079,0.00005200112,0.0000423965,0.00009975515,0.0002356345,0.001692508],"category_scores_gemma":[0.000009513245,0.0001293169,0.0000241528,0.00003718692,0.0001570952,0.00001442847,0.0001319505,0.0003093116,0.00001335349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002449128,"about_ca_system_score_gemma":0.00001704907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006535545,"about_ca_topic_score_gemma":0.00003125375,"domain_scores_codex":[0.9990267,0.00001629265,0.00009394556,0.0003552849,0.0001911006,0.0003167203],"domain_scores_gemma":[0.9995639,0.00003723377,0.00007369304,0.0001980947,0.00001629683,0.0001108112],"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":[0.001156419,0.001646313,0.09317078,0.01163894,0.005012619,0.002127816,0.0008909091,0.000007315939,0.04588264,0.01117648,0.4504108,0.3768789],"study_design_scores_gemma":[0.006816566,0.0004687709,0.001145442,0.005652539,0.000311053,0.0001779626,0.000530721,0.0002682627,0.01728623,0.0008871903,0.9638594,0.002595831],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01982677,0.004397051,0.0004688237,0.0004443195,0.00007158022,0.0006163977,0.0001097112,0.000389731,0.9736756],"genre_scores_gemma":[0.2684507,0.001007376,0.0009533117,0.00008696718,0.002913674,0.0001566421,0.00004450722,0.0004344476,0.7259524],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5134486,"threshold_uncertainty_score":0.9992201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343763308470892,"score_gpt":0.245411415802374,"score_spread":0.2319737827176651,"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."}}