{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006218313,0.002066132,0.0009975572,0.003768262,0.0007261456,0.002033298,0.001635131,0.0007830249,0.1549717],"category_scores_gemma":[0.003289812,0.0005942592,0.0008571143,0.006435894,0.0002015765,0.001072917,0.001353281,0.001108735,0.1997411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001263846,"about_ca_system_score_gemma":0.001880067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02245949,"about_ca_topic_score_gemma":0.02639192,"domain_scores_codex":[0.9990566,0.0001065817,0.0001241313,0.0002792711,0.0002863801,0.0001470129],"domain_scores_gemma":[0.9980111,0.0003024463,0.0002199229,0.0004807257,0.0008125522,0.0001732598],"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":[0.00006658511,0.00001384289,0.00153355,0.0003526365,0.00002367238,0.00002447041,0.00001419253,0.0001853234,0.0002305119,0.0004781063,0.9924732,0.004603836],"study_design_scores_gemma":[0.00007262473,0.00001262175,0.007358538,0.0001159159,0.00001811796,0.00005146315,0.00005601043,0.0002744498,0.0006233551,0.0007140792,0.9906842,0.00001876451],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001160528,0.00001884289,0.00004877585,0.00001817843,0.000009318112,0.000006031494,0.9983771,0.0002358132,0.001169913],"genre_scores_gemma":[0.0002714518,0.00002249521,0.0001158232,0.00001635184,0.000003063501,0.00002253463,0.9987072,0.00004191028,0.0007991191],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8450283,"threshold_uncertainty_score":0,"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."}}