{"id":"W2992360793","doi":"","title":"Collaborative Forecasting: Goodyear Tire & Rubber Company's Journey","year":2004,"lang":"en","type":"article","venue":"The Journal of Business Forecasting Methods & Systems","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Product (mathematics); Negotiation; Demand forecasting; Production (economics); Distribution (mathematics); Process (computing); Marketing; Operations research; Engineering; Business; Operations management; Computer science; Economics; 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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.02943967,0.0004258191,0.001141657,0.0005641151,0.0009111272,0.0007064228,0.002213144,0.000186678,0.00005535584],"category_scores_gemma":[0.0120268,0.0002406837,0.0002913419,0.004533248,0.0003475207,0.0006656389,0.0003117982,0.0007594447,0.0000455326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002354914,"about_ca_system_score_gemma":0.0006183118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002237073,"about_ca_topic_score_gemma":0.00002434831,"domain_scores_codex":[0.992291,0.001935601,0.002838864,0.0003925396,0.001927826,0.0006141245],"domain_scores_gemma":[0.9830785,0.005257816,0.004526449,0.0009773877,0.005878981,0.0002808723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00108736,0.0008156983,0.002906677,0.0002799001,0.0006718332,0.0002684536,0.01625837,0.3839572,0.01259248,0.02172957,0.03794175,0.5214907],"study_design_scores_gemma":[0.008197616,0.002094151,0.009619263,0.007631807,0.001449517,0.0415306,0.03608069,0.3147771,0.009452767,0.2184741,0.347352,0.003340327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1772827,0.0012689,0.811354,0.002367848,0.002243334,0.0008565814,0.00003057164,0.0001130397,0.004482973],"genre_scores_gemma":[0.7795662,0.00004840904,0.2187449,0.00008774399,0.001018727,0.00002022068,0.000001956009,0.00006502872,0.0004467876],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6022835,"threshold_uncertainty_score":0.9993961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2824411372917397,"score_gpt":0.4440060144271958,"score_spread":0.1615648771354561,"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."}}