{"id":"W2027050307","doi":"10.1016/j.jclepro.2006.07.026","title":"ReSICLED: a new recovery-conscious design method for complex products based on a multicriteria assessment of the recoverability","year":2006,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact","funders":"","keywords":"Product (mathematics); Computer science; Strengths and weaknesses; Product design; Risk analysis (engineering); Systems engineering; Industrial engineering; Engineering; Reliability engineering; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.001170704,0.0001243999,0.0002291207,0.0001084139,0.00006517892,0.00003365837,0.0001264408,0.00005108799,0.00001502848],"category_scores_gemma":[0.0003384611,0.0000892706,0.0001001324,0.0001457751,0.00001846942,0.0001768583,0.0000074292,0.0001534824,2.077365e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001423899,"about_ca_system_score_gemma":0.0001202839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002485645,"about_ca_topic_score_gemma":0.000008519399,"domain_scores_codex":[0.9988176,0.0001348715,0.00051426,0.0001636483,0.0002414838,0.0001280973],"domain_scores_gemma":[0.9989568,0.0001126004,0.0003396088,0.0002571607,0.0003051887,0.00002861608],"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":[0.000219978,0.00008804347,0.0000936717,0.0002065926,0.00001880005,2.128374e-7,0.00003904328,0.9519247,0.0251268,0.000009644498,0.008906618,0.01336589],"study_design_scores_gemma":[0.001278799,0.0004901012,0.02138177,0.0001819259,0.0001085005,0.00002624353,0.00001921224,0.6342607,0.3326284,0.002272603,0.007143281,0.0002085143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04715261,0.00003941706,0.9483578,0.002079326,0.00144488,0.0007336099,0.000005620097,0.00003705737,0.000149731],"genre_scores_gemma":[0.5891452,0.000007815891,0.4100356,0.00003142163,0.000570216,0.000006643118,0.000003027958,0.00002291182,0.0001771341],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5419925,"threshold_uncertainty_score":0.364035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02895544524592344,"score_gpt":0.2817565144047478,"score_spread":0.2528010691588244,"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."}}