{"id":"W4231764799","doi":"10.1002/sam.11387","title":"Issue Information","year":2019,"lang":"en","type":"paratext","venue":"Statistical Analysis and Data Mining The ASA Data Science Journal","topic":"Human auditory perception and evaluation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Université de Montréal","funders":"","keywords":"Computer science; Information retrieval; Citation; World Wide Web; Data science","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004119816,0.0001968899,0.0003530644,0.000520993,0.0005979338,0.001837216,0.003099645,0.00008266781,0.04040167],"category_scores_gemma":[0.0005704757,0.0001294031,0.00002889063,0.0009026439,0.0004042732,0.003911602,0.001092211,0.0005290415,0.02121925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006559319,"about_ca_system_score_gemma":0.0002254406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009407612,"about_ca_topic_score_gemma":0.00002966986,"domain_scores_codex":[0.997686,0.00007561005,0.0005684084,0.0003797703,0.0009719082,0.0003182471],"domain_scores_gemma":[0.9972966,0.0001914361,0.0002088785,0.001972525,0.0001426694,0.0001878668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002747596,0.00000370663,0.0000302931,0.00002394694,0.000167485,5.385216e-7,0.0002447423,0.002654356,0.00001178591,0.00000830256,0.9549817,0.04187043],"study_design_scores_gemma":[0.00006819697,0.00001193943,0.002454549,0.00002198957,0.0004994433,0.000011963,0.0004538442,0.5135813,4.199234e-7,0.00001160851,0.4827425,0.000142217],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.0009747503,0.0004071927,0.9526601,0.0004204595,0.006845149,0.0001803465,0.0254738,0.00003762413,0.01300057],"genre_scores_gemma":[0.08468768,0.03207391,0.2914493,0.003603202,0.01937249,0.00002470186,0.516661,0.0002211992,0.0519065],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6612108,"threshold_uncertainty_score":0.999199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07162451266438453,"score_gpt":0.3683286561938265,"score_spread":0.296704143529442,"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."}}