{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001077919,0.001209461,0.001065109,0.001188745,0.0003156309,0.001023893,0.001228403,0.0006950751,0.002381606],"category_scores_gemma":[0.001622762,0.000572918,0.000931273,0.0003386653,0.0004589208,0.001193411,0.0009852645,0.0007000183,0.0005305589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005248249,"about_ca_system_score_gemma":0.0008907032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006829785,"about_ca_topic_score_gemma":0.001570987,"domain_scores_codex":[0.9989766,0.000174363,0.00004836782,0.000185801,0.0005671354,0.00004786472],"domain_scores_gemma":[0.999278,0.0001954695,0.000135932,0.0001220426,0.0002488518,0.00001972651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000359845,0.0002242226,0.001156326,0.0004810512,0.0001726981,0.000119473,0.0001220054,0.2181347,0.1554496,0.01618116,0.001999536,0.6055993],"study_design_scores_gemma":[0.00003526638,0.0002612559,0.0004780284,0.0000201146,0.00005206797,0.0001049246,0.00001056098,0.9512432,0.03923326,0.003770379,0.004747127,0.00004369752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003932359,0.00005402468,0.9944493,0.00001821603,0.00001321331,0.00002940124,0.00001360653,0.0005567355,0.0009331544],"genre_scores_gemma":[0.2216109,0.0001018257,0.7743905,0.00008604776,0.00002593744,0.0001927574,0.0001013499,0.0002590183,0.003231743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002381606,"threshold_uncertainty_score":0.007967234,"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."}}