{"id":"W2737069831","doi":"","title":"Δυναμικά μοντέλα χωροθέτησης για το σχεδιασμό δικτύου αντίστροφης εφοδιαστικής αλυσίδας","year":2015,"lang":"el","type":"article","venue":"","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reverse logistics; Spare part; Remanufacturing; Original equipment manufacturer; Time horizon; Business; Reuse; Operations research; Operations management; Competitive advantage; Computer science; Supply chain; Manufacturing engineering; Engineering; Marketing","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":[],"consensus_categories":[],"category_scores_codex":[0.001690719,0.0006504721,0.0007029517,0.00103822,0.001182075,0.004298165,0.001238783,0.002109248,0.02007616],"category_scores_gemma":[0.004207429,0.0006931263,0.0007389812,0.001255402,0.001970046,0.003587045,0.00150411,0.002152506,0.00382991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001557128,"about_ca_system_score_gemma":0.001889014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00264905,"about_ca_topic_score_gemma":0.002830867,"domain_scores_codex":[0.9985843,0.0004049372,0.00005345025,0.0002657715,0.0005175009,0.0001741807],"domain_scores_gemma":[0.9979977,0.001044282,0.000316867,0.0001596153,0.0003412343,0.0001403451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005585416,0.000806737,0.009909383,0.001379456,0.0001648616,0.002033941,0.005271733,0.160192,0.01873313,0.4504732,0.01614805,0.3343289],"study_design_scores_gemma":[0.0001450519,0.0004864431,0.01085848,0.0008487405,0.0001399156,0.001527981,0.006964927,0.1196636,0.008839327,0.4872237,0.3630489,0.0002531482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1265034,0.004732088,0.5198013,0.0119352,0.0006331684,0.0004254259,0.001327104,0.0004007547,0.3342415],"genre_scores_gemma":[0.813861,0.006636602,0.1064069,0.0009971617,0.0002766302,0.0005638222,0.0005192137,0.0002004232,0.0705382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02007616,"threshold_uncertainty_score":0.06716144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03969363536851896,"score_gpt":0.2276689036966622,"score_spread":0.1879752683281432,"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."}}