{"id":"W6925186628","doi":"10.17182/hepdata.44234.v1/t2","title":"Table 2","year":2000,"lang":"en","type":"dataset","venue":"HEPData","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; McGill University","funders":"","keywords":"Meson; Table (database); Luminosity; Photon; Momentum (technical analysis); Sample (material)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005578463,0.001662148,0.00098714,0.003352053,0.0006369065,0.001861817,0.001419433,0.0008785077,0.1009406],"category_scores_gemma":[0.003617706,0.0003916412,0.0008531359,0.005258951,0.0002303925,0.0008432636,0.0009165464,0.001311236,0.1159398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001585856,"about_ca_system_score_gemma":0.001802877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0228598,"about_ca_topic_score_gemma":0.02878219,"domain_scores_codex":[0.9989359,0.00009689812,0.000134227,0.000377452,0.000296504,0.0001590009],"domain_scores_gemma":[0.9978903,0.0003222998,0.0002571339,0.0004947124,0.0008564014,0.0001790854],"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":[0.0001336947,0.00004018096,0.004938593,0.000492272,0.0000443123,0.00003617182,0.00001982612,0.0004015716,0.0003970565,0.0006874389,0.9867353,0.006073501],"study_design_scores_gemma":[0.0001089987,0.00002539391,0.01879744,0.0001369898,0.00002903617,0.00009753966,0.00007979898,0.0004008481,0.0007425983,0.0006380808,0.9789231,0.00002016457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002710922,0.00002355215,0.00005097234,0.00002351045,0.00001448191,0.000009711167,0.9983462,0.0001456988,0.001114813],"genre_scores_gemma":[0.0005350393,0.00002255234,0.0001432282,0.00002402663,0.00000468094,0.00003015952,0.9981412,0.00002966924,0.001069466],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8990594,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02648624039813519,"score_gpt":0.2661506052207253,"score_spread":0.2396643648225901,"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."}}