{"id":"W2336583268","doi":"","title":"First year of data taking at high energy for MoEDAL","year":2016,"lang":"en","type":"article","venue":"CERN Document Server (European Organization for Nuclear Research)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006183909,0.0001213071,0.0001797551,0.0003151833,0.0008492654,0.0006825798,0.003884745,0.00003364041,0.006095687],"category_scores_gemma":[0.004700828,0.00008518422,0.00005740565,0.0008353782,0.0001790806,0.0008278306,0.006307493,0.00004308156,0.001540935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001459928,"about_ca_system_score_gemma":0.00001535653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004787807,"about_ca_topic_score_gemma":0.00001991229,"domain_scores_codex":[0.9964789,0.0002718093,0.0005534403,0.000976119,0.001351787,0.0003679714],"domain_scores_gemma":[0.995755,0.0005977098,0.0003360321,0.002341606,0.0008321833,0.0001374554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000186228,0.0001508685,0.0007738202,0.00005983391,0.00007457495,0.000004633055,0.0003504554,0.0001095511,0.0002684149,0.6222603,0.3452159,0.0305455],"study_design_scores_gemma":[0.001837346,0.0002302905,0.004892645,0.00009581669,0.00002305821,0.000003713425,0.0003473471,0.0001993213,0.00127724,0.07407519,0.9167413,0.0002767044],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9337585,0.0001021084,0.04067425,0.01452153,0.002556386,0.001933272,0.0005593799,0.0006268428,0.005267716],"genre_scores_gemma":[0.9839821,0.00002102103,0.0003177944,0.00006501797,0.000141343,5.221111e-7,0.0002954979,0.0001141404,0.01506254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5715255,"threshold_uncertainty_score":0.9992365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1656825639126309,"score_gpt":0.3618251756657265,"score_spread":0.1961426117530956,"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."}}