{"id":"W7000403776","doi":"","title":"Evidence for D0-DÌ0 mixing","year":2007,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"SLAC National Accelerator Laboratory; Institut National de Physique Nucléaire et de Physique des Particules; U.S. Department of Energy; European Commission; Institute of High Energy Physics; Centre National de la Recherche Scientifique; Bundesministerium für Bildung und Forschung; Natural Sciences and Engineering Research Council of Canada; Alfred P. Sloan Foundation; Deutsche Forschungsgemeinschaft; Ministerio de Economía y Competitividad; National Science Foundation","keywords":"Mixing (physics); Measure (data warehouse); Detector; Mixing ratio; Linear particle accelerator","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005389161,0.0003292063,0.0002126735,0.0008704006,0.0005120733,0.0005382549,0.0002900234,0.000332878,0.004789702],"category_scores_gemma":[0.001484797,0.0002091336,0.0001762749,0.0008452507,0.0003815426,0.0002310154,0.000666648,0.0002203862,0.0006818749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001874752,"about_ca_system_score_gemma":0.0001698275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001143604,"about_ca_topic_score_gemma":0.001146251,"domain_scores_codex":[0.9997098,0.00004590744,0.00003308238,0.00008706327,0.00005728538,0.00006672471],"domain_scores_gemma":[0.9991123,0.0002560294,0.0002588933,0.00009193899,0.0001553645,0.0001254473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002889779,0.0001443565,0.8131418,0.000242231,0.0001510193,0.0008425468,0.001224611,0.0001887903,0.1568465,0.003303965,0.000957486,0.020067],"study_design_scores_gemma":[0.0001168932,0.0005799809,0.9347849,0.00005284683,0.0001493305,0.003013446,0.0007563399,0.001160763,0.05002656,0.002830066,0.006481571,0.00004730455],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951786,0.000272581,0.0005362651,0.00007013569,0.000006853724,0.000004500319,0.0005805934,0.00002674035,0.003323813],"genre_scores_gemma":[0.9985808,0.00007268196,0.0002908648,0.00004092792,0.000004902083,0.000005316286,0.0003642547,0.000003993343,0.000636281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004789702,"threshold_uncertainty_score":0.01602316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04670664967051328,"score_gpt":0.2986254525899308,"score_spread":0.2519188029194175,"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."}}