{"id":"W4244312203","doi":"10.1088/1742-6596/1650/1/011001","title":"Preface","year":2020,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gratitude; Library science; Event (particle physics); Computer science; Political science; Operations research; Psychology; Engineering; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.001210954,0.00008149869,0.0002345596,0.00004752388,0.00008105816,0.0006007458,0.001063855,0.0000158062,0.0002486593],"category_scores_gemma":[0.00160188,0.00005513622,0.0001042034,0.0005252672,0.00009309874,0.0009331763,0.0002592469,0.0001389681,0.0001829104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007626321,"about_ca_system_score_gemma":0.000123348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001443697,"about_ca_topic_score_gemma":0.000001088335,"domain_scores_codex":[0.9979047,0.00008120562,0.0005344509,0.0002101422,0.001143586,0.0001259613],"domain_scores_gemma":[0.9980927,0.0002040398,0.0005191643,0.0003156049,0.000725582,0.0001428996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000102925,0.00006098054,0.00141173,0.00001092868,0.00004252618,0.00002976282,0.004521224,0.001235553,0.003493306,0.07828593,0.1329986,0.7778065],"study_design_scores_gemma":[0.0008229146,0.0009409299,0.006331186,0.00007933512,0.00005381319,0.0000366822,0.01155598,0.005541025,0.06726863,0.3559802,0.5509625,0.0004268348],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1597363,0.0001080621,0.7933112,0.02946695,0.002165549,0.0001212962,0.00002454389,0.00004350922,0.0150226],"genre_scores_gemma":[0.9952052,0.000008022738,0.003202713,0.000365809,0.0003543733,1.979854e-7,6.589261e-7,0.00000341292,0.0008595727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8354689,"threshold_uncertainty_score":0.5793006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2716332034354314,"score_gpt":0.3749687262457206,"score_spread":0.1033355228102892,"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."}}