{"id":"W6995923920","doi":"","title":"Predictive models can lose the plot. Here's how to keep them on track","year":2023,"lang":"en","type":"article","venue":"CERES (Cranfield University)","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pace; Analytics; Track (disk drive); Launched; Predictive analytics; Quarter (Canadian coin); Online algorithm; Business model; Information technology; Technology forecasting","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02088562,0.003181187,0.002341961,0.003603293,0.003667698,0.02070069,0.004472319,0.008557878,0.0234682],"category_scores_gemma":[0.1089446,0.001610459,0.002268672,0.002792927,0.01265437,0.0483274,0.009272195,0.02923801,0.01641009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003128002,"about_ca_system_score_gemma":0.003599729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009507822,"about_ca_topic_score_gemma":0.007183439,"domain_scores_codex":[0.9893429,0.003767594,0.0004884306,0.001570539,0.004401771,0.0004289007],"domain_scores_gemma":[0.9356712,0.04466278,0.002198198,0.007922571,0.007883108,0.001662079],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001918663,0.0001267722,0.004129388,0.0007408588,0.0004031225,0.0002252457,0.0007480778,0.007489109,0.0003488371,0.2633406,0.4496533,0.2726028],"study_design_scores_gemma":[0.00007983887,0.00009707688,0.0007478002,0.001640712,0.0001079439,0.0001646162,0.0008432179,0.01761116,0.0003706048,0.5622459,0.4159112,0.0001798277],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.002948301,0.0471308,0.2051597,0.6641168,0.03263482,0.0001569405,0.001280327,0.005330026,0.04124225],"genre_scores_gemma":[0.2305524,0.1016651,0.2638961,0.2346663,0.06871307,0.000784833,0.002696574,0.00867994,0.08834573],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9791144,"threshold_uncertainty_score":0.110455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09812134343303225,"score_gpt":0.2292767621662081,"score_spread":0.1311554187331759,"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."}}