{"id":"W4386838816","doi":"","title":"SPARE PARTS INVENTORY CONTROL BASED ADDITIVE MANUFACTURING","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Spare part; Inventory control; Manufacturing engineering; Computer science; Control (management); Engineering; Operations management; Artificial intelligence","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"],"consensus_categories":[],"category_scores_codex":[0.001013126,0.0004260692,0.0004199456,0.0001521575,0.0001895933,0.000316721,0.0007387179,0.0003047175,0.0004033532],"category_scores_gemma":[0.0003413082,0.0004894055,0.0001902826,0.0001132516,0.0000878345,0.0001246878,0.0003382452,0.0007551934,0.0000518814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001523075,"about_ca_system_score_gemma":0.000124276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001316144,"about_ca_topic_score_gemma":0.0002147224,"domain_scores_codex":[0.9971728,0.0010439,0.000451923,0.0006214036,0.0003548261,0.0003551434],"domain_scores_gemma":[0.9975101,0.0004584994,0.0002452442,0.001049931,0.0004951952,0.0002410804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005335474,0.0003919256,0.0006822987,0.003252157,0.0005214607,0.00004588283,0.01112771,0.8897258,0.0002819567,0.006572363,0.01080802,0.07653708],"study_design_scores_gemma":[0.0008732402,3.489359e-7,0.001178234,0.00173116,0.00008773973,0.000001887362,0.00005101369,0.7939971,0.1732399,0.001789065,0.02629156,0.0007586714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01196664,0.0009032389,0.941671,0.003550891,0.0005106687,0.0007253696,0.0003190543,0.001399293,0.03895391],"genre_scores_gemma":[0.9851924,0.000283779,0.01234015,0.0001819256,0.00005942786,0.00014957,0.001058274,0.000100232,0.0006342319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9732258,"threshold_uncertainty_score":0.9997557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01253249482340211,"score_gpt":0.1971587677938394,"score_spread":0.1846262729704373,"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."}}