{"id":"W2771098580","doi":"10.1111/jtsa.12280","title":"Editorial, January 2018","year":2017,"lang":"en","type":"article","venue":"Journal of Time Series Analysis","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Editorial board; Audience measurement; Nonparametric statistics; Econometrics; Library science; Mathematics; Computer science; Political 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":[],"consensus_categories":[],"category_scores_codex":[0.002608602,0.0000869292,0.0004329013,0.0003788446,0.0005460263,0.0007600811,0.001613232,0.00006924182,0.0009049118],"category_scores_gemma":[0.00225005,0.00005671358,0.0005772971,0.0005278236,0.0001601274,0.0008134594,0.0001803137,0.0001480305,0.0002056337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002403671,"about_ca_system_score_gemma":0.00005497911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005555968,"about_ca_topic_score_gemma":0.00002416743,"domain_scores_codex":[0.9978773,0.00004901147,0.000735359,0.000152691,0.001058585,0.0001270556],"domain_scores_gemma":[0.9960384,0.0001907977,0.001782078,0.0009982896,0.0008817417,0.0001087443],"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":[0.00002449623,0.00002290948,0.002872633,4.105661e-7,0.0002366944,0.000003301382,0.00003023269,0.0001560953,0.0003343831,0.0001639092,0.9928088,0.00334616],"study_design_scores_gemma":[0.0001099873,0.0001552905,0.007221324,0.000008845184,0.0006061887,0.00001848287,0.00008888569,0.001178232,0.0005214814,0.02635741,0.9636137,0.0001201649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3788745,0.001163115,0.1723673,0.1086741,0.1198535,0.0008773428,0.0003565936,0.0003272829,0.2175064],"genre_scores_gemma":[0.686555,0.0004571881,0.1081328,0.00025332,0.12665,0.000009804165,0.000008574637,0.00004219942,0.07789119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3076805,"threshold_uncertainty_score":0.990815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05976159058930415,"score_gpt":0.3877744663193208,"score_spread":0.3280128757300167,"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."}}