{"id":"W6906431522","doi":"10.17182/hepdata.46115.v1/t29","title":"Table 29","year":2006,"lang":"en","type":"dataset","venue":"HEPData","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; McGill University","funders":"","keywords":"Hadron; HERA; Luminosity; Lambda; Table (database); Energy (signal processing)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003085847,0.0004177158,0.000448576,0.0002234859,0.0000944635,0.0001623363,0.001718704,0.0003818948,0.006225416],"category_scores_gemma":[0.0001350863,0.0004211472,0.0000640475,0.0004435937,0.00008384581,0.0002407105,0.0007674425,0.0006160698,0.2432701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009113536,"about_ca_system_score_gemma":0.0002194694,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01225597,"about_ca_topic_score_gemma":0.007855504,"domain_scores_codex":[0.9977173,0.00007481673,0.0003400733,0.0007187169,0.0005612996,0.0005877802],"domain_scores_gemma":[0.9957412,0.00004630641,0.0002409522,0.003800345,0.00005445471,0.0001167095],"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":[0.000009110748,0.0001062114,0.000008182368,0.00008804554,0.00003095332,0.0001253013,2.80116e-7,0.000001921573,0.00001368926,0.000008291331,0.9995902,0.00001784532],"study_design_scores_gemma":[0.0002325327,0.00001373827,0.00002586124,0.00006518841,0.0001288217,0.00002636456,0.000001109461,0.000005418056,0.00002034712,0.00003527362,0.9989765,0.0004688077],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000001517967,0.0005537691,0.000001808788,0.00001838083,0.0004862334,0.0002381036,0.9959497,0.0001672992,0.002583142],"genre_scores_gemma":[3.397191e-7,0.0000552614,0.0001493453,0.00017669,0.0008376146,0.00003099558,0.9945287,0.0001243096,0.004096788],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2370447,"threshold_uncertainty_score":0.999824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02604175787122871,"score_gpt":0.2798891864650323,"score_spread":0.2538474285938036,"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."}}