{"id":"W4205685700","doi":"10.1007/978-3-030-85855-1_8","title":"Conclusion and Advanced Topics","year":2022,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Censoring (clinical trials); Data science; Artificial intelligence; Analytics; Machine learning; Econometrics; Mathematics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001110635,0.0002791386,0.0003750524,0.0004332907,0.0002374771,0.0001219593,0.0008175981,0.0001103126,0.00287227],"category_scores_gemma":[0.00005553081,0.0002638208,0.00008851534,0.0001544451,0.0001695909,0.0001543267,0.002850715,0.0003382627,0.0000378264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001432559,"about_ca_system_score_gemma":0.00001505342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001482211,"about_ca_topic_score_gemma":0.00007414089,"domain_scores_codex":[0.9974375,0.00002920289,0.0006426772,0.0007823783,0.0008624872,0.0002457741],"domain_scores_gemma":[0.99853,0.0001134326,0.0002665683,0.0009750635,0.00005215918,0.00006281919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001924763,0.000009890956,0.00009980847,0.00002700533,0.00001116206,0.00004663152,0.0001719069,0.00004134751,0.000003226254,0.8256619,0.004690686,0.1692172],"study_design_scores_gemma":[0.0001251786,0.00005499643,0.0002356653,0.0000550118,0.000008898447,0.000004105451,0.0001695664,0.00006981237,0.000009369011,0.2000639,0.7989818,0.0002217264],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004193106,0.0006011644,0.000818178,0.00464875,0.0004360366,0.001177721,0.00005456337,0.0001531723,0.9916911],"genre_scores_gemma":[0.007280079,0.002505291,0.02212292,0.0003981042,0.0001046426,0.0002826471,0.00003664168,0.00005806108,0.9672116],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7942911,"threshold_uncertainty_score":0.9999814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04076060501957447,"score_gpt":0.3116947197022129,"score_spread":0.2709341146826384,"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."}}