{"id":"W4398619581","doi":"10.7910/dvn/28075/x6loab","title":"events.2010.20150313084533.tab.zip","year":2015,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Event (particle physics); Computer science; Physics","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":[0.0007476734,0.001683649,0.0009715714,0.004679446,0.0006258401,0.002551813,0.001794531,0.001310825,0.1639337],"category_scores_gemma":[0.004795665,0.0008248676,0.0007817571,0.009244343,0.0003577322,0.001367862,0.001524702,0.001312935,0.1805583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001867938,"about_ca_system_score_gemma":0.002094625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02843331,"about_ca_topic_score_gemma":0.04407142,"domain_scores_codex":[0.99928,0.00006979957,0.000107976,0.0001936305,0.0001850379,0.0001636837],"domain_scores_gemma":[0.9979619,0.0004561432,0.0003526931,0.0004227669,0.0005297732,0.0002767548],"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":[0.00003576884,0.00001109012,0.0007450787,0.0001848741,0.000008873933,0.00001091674,0.00001344009,0.0001324794,0.00004719151,0.0005226713,0.9969829,0.001304731],"study_design_scores_gemma":[0.0001944469,0.00001367405,0.005485035,0.0001842047,0.00001468777,0.00004563923,0.00006076998,0.000290562,0.0003042864,0.001050199,0.9923349,0.0000215699],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007897615,0.00002015066,0.00002784942,0.0000368107,0.00001332251,0.000004502945,0.9987827,0.0001723151,0.0008634663],"genre_scores_gemma":[0.0003769419,0.00003874262,0.00008276647,0.00003318019,0.000008177316,0.0000251794,0.9983411,0.0000660669,0.001027903],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8360662,"threshold_uncertainty_score":0.548413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09663233296670543,"score_gpt":0.3397779988789366,"score_spread":0.2431456659122312,"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."}}