{"id":"W6910561918","doi":"10.48660/04070006","title":"Maximum likelihood and efficient use of quantum resources in the alignment of reference frames","year":2004,"lang":"en","type":"other","venue":"PIRSA","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Frame (networking); Maximum likelihood; Quantum; Feature (linguistics); Identification (biology); Pattern recognition (psychology)","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":[0.0004443301,0.0003029129,0.0005220075,0.0003927569,0.00001718971,0.00002815271,0.0004090935,0.0002531193,0.0002374024],"category_scores_gemma":[0.00009613101,0.0002070247,0.0000625864,0.0002984647,0.0003018617,0.00001806251,0.0001340066,0.0002541563,0.0001230583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007308869,"about_ca_system_score_gemma":0.00006474263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00428951,"about_ca_topic_score_gemma":0.0007024771,"domain_scores_codex":[0.9980185,0.0002038012,0.0004224641,0.0003803179,0.0006751909,0.0002997059],"domain_scores_gemma":[0.9984635,0.0001564991,0.0005561995,0.0007425397,0.00003300832,0.00004828066],"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":[0.001677176,0.01417247,0.04512984,0.008403755,0.001905462,0.0003301664,0.1187705,0.003824832,0.01726866,0.05618975,0.7162262,0.01610121],"study_design_scores_gemma":[0.001977512,0.0005069404,0.02063557,0.004787149,0.0002422625,0.00001226705,0.002160125,0.0002177242,0.0009318442,0.002675252,0.965065,0.0007883267],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.738875,0.01647172,0.0001722167,0.0003206806,0.0002647001,0.003119493,0.002633487,0.0002463087,0.2378963],"genre_scores_gemma":[0.9927649,0.0003800458,0.0007059649,0.00007602234,0.00006307234,0.00004662445,0.00003671299,0.0005780674,0.005348545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2538899,"threshold_uncertainty_score":0.8442222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02893340252284826,"score_gpt":0.2571141193328959,"score_spread":0.2281807168100476,"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."}}