{"id":"W4243852512","doi":"10.1088/1755-1315/565/1/011001","title":"Preface","year":2020,"lang":"en","type":"article","venue":"IOP Conference Series Earth and Environmental Science","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Excellence; Library science; Commercialization; Engineering; Political science; Computer science; Law","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":[],"category_scores_codex":[0.0006502051,0.0001340572,0.0002028941,0.00006645385,0.0004887769,0.0004298937,0.0007401415,0.0000347766,0.001721878],"category_scores_gemma":[0.0003381638,0.00009799672,0.00005078059,0.0006481137,0.001789287,0.001277695,0.0003713422,0.0001081887,0.0005412503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009411305,"about_ca_system_score_gemma":0.00006348677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002061316,"about_ca_topic_score_gemma":0.00002638549,"domain_scores_codex":[0.9974443,0.00005151275,0.0002876493,0.0006672873,0.001224514,0.0003247271],"domain_scores_gemma":[0.9990289,0.0000663296,0.00009308532,0.0003044,0.00002156696,0.0004857264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001401959,0.00005282019,0.02322802,0.000004804192,0.0000136924,0.0000251796,0.006820776,0.0004798998,0.3844724,0.005573482,0.0004039856,0.5787848],"study_design_scores_gemma":[0.0006768389,0.0008224039,0.5529389,0.00001258073,0.00003321065,0.00005297314,0.02137338,0.0186484,0.2160498,0.01139799,0.1770635,0.0009300747],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844339,0.0001307146,0.0006466931,0.006862922,0.00006093061,0.00008078814,0.00002411789,0.00002457326,0.0077353],"genre_scores_gemma":[0.996621,0.0005122187,0.0008447337,0.0006275874,0.00003058452,0.000002256862,0.000002155482,0.000003242563,0.00135626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5778547,"threshold_uncertainty_score":0.9991907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05215576437707153,"score_gpt":0.2742579843563538,"score_spread":0.2221022199792823,"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."}}