{"id":"W3124908351","doi":"","title":"Examining Collaborative Green Supply Chains Through the Lens of Proximity Economics","year":2013,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Typology; Supply chain; Dimension (graph theory); Sample (material); Field (mathematics); Business; Knowledge management; Industrial organization; Marketing; Sociology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002365724,0.000496566,0.0003700138,0.004677501,0.002984886,0.007941859,0.0008926585,0.001583283,0.005905823],"category_scores_gemma":[0.006578064,0.0003588875,0.0004301748,0.0058713,0.009688697,0.01198767,0.006344856,0.001512996,0.0002531467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00374623,"about_ca_system_score_gemma":0.002148335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003653072,"about_ca_topic_score_gemma":0.003196546,"domain_scores_codex":[0.996858,0.002200635,0.00006377407,0.0002236947,0.0004442457,0.0002096613],"domain_scores_gemma":[0.9937168,0.004652853,0.0006935669,0.0004176492,0.0003051466,0.0002140532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001991653,0.00003296112,0.002605037,0.0001579533,0.0000168447,0.0005100755,0.01726341,0.003227617,0.0004546285,0.9573869,0.0003748183,0.0179498],"study_design_scores_gemma":[0.00001644764,0.00005140743,0.005011939,0.0003492064,0.00002897935,0.0006922949,0.06854466,0.01248308,0.0008646758,0.8453738,0.06655619,0.00002733446],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3742652,0.007031117,0.3463342,0.009263013,0.0001337656,0.0002509399,0.0001910006,0.00007530343,0.2624554],"genre_scores_gemma":[0.9674833,0.002519884,0.02614712,0.000102375,0.00004627038,0.0001014206,0.00002958535,0.00001645987,0.003553576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007941859,"threshold_uncertainty_score":0.02718091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02277189080415767,"score_gpt":0.2119831683078808,"score_spread":0.1892112775037231,"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."}}